{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9c3a5e62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch    : 1.12.1\n",
      "lightning: 2022.9.15\n",
      "\n"
     ]
    }
   ],
   "source": [
    "%load_ext watermark\n",
    "%watermark -p torch,lightning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "292759a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import lightning as L\n",
    "import torch\n",
    "import torch.nn.functional as F\n",
    "import torchmetrics\n",
    "from lightning.pytorch.loggers import CSVLogger\n",
    "\n",
    "from shared_utilities import CustomDataModule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ef478510-97a2-497c-8831-bb594b753d85",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_epochs = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbcee9b9-40cf-4083-b36e-b09fe28e4ee2",
   "metadata": {},
   "source": [
    "### With Restarts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f9bf7772",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs/10)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "for i in range(num_epochs):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "plt.ylabel(\"Learning rate\")\n",
    "plt.xlabel(\"Epoch\")\n",
    "plt.plot(lrs);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce656fef-698a-4d9e-8a2e-0c4e8b67d01b",
   "metadata": {},
   "source": [
    "### Classic cosine annealing (decay per epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0271fa05-1191-4dfa-8f57-c1e9310112ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_epochs)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "\n",
    "for i in range(num_epochs):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "plt.plot(lrs)\n",
    "plt.xlabel('Epoch')\n",
    "plt.savefig('4-cosine-epoch-decay_lr.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff5603b4-e089-4489-a51c-1cb41cdf9d27",
   "metadata": {},
   "source": [
    "### Classic cosine annealing (decay per batch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6d9c70b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "model = torch.nn.Linear(1, 1)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.1)\n",
    "\n",
    "\n",
    "dm = CustomDataModule()\n",
    "dm.setup(\"training\")\n",
    "num_steps = num_epochs * len(dm.train_dataloader())\n",
    "scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=num_steps)\n",
    "lrs = []\n",
    "\n",
    "\n",
    "for i in range(num_steps):\n",
    "    optimizer.step()\n",
    "    lrs.append(optimizer.param_groups[0][\"lr\"])\n",
    "    scheduler.step()\n",
    "\n",
    "\n",
    "ax1 = plt.subplot(1, 1, 1)\n",
    "ax1.set_ylabel(\"Learning rate\")\n",
    "ax1.set_xlabel(\"Iterations\")\n",
    "ax1.plot(lrs)\n",
    "\n",
    "###################\n",
    "# Set second x-axis\n",
    "ax2 = ax1.twiny()\n",
    "newlabel = list(range(num_epochs+1))\n",
    "\n",
    "newpos = [e * (num_steps // num_epochs) for e in newlabel]\n",
    "\n",
    "ax2.set_xticks(newpos[::10])\n",
    "ax2.set_xticklabels(newlabel[::10])\n",
    "\n",
    "ax2.xaxis.set_ticks_position('bottom')\n",
    "ax2.xaxis.set_label_position('bottom')\n",
    "ax2.spines['bottom'].set_position(('outward', 45))\n",
    "ax2.set_xlabel('Epochs')\n",
    "ax2.set_xlim(ax1.get_xlim());\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ce808943-a20e-44d2-9303-c897226b37df",
   "metadata": {},
   "outputs": [],
   "source": [
    "class PyTorchMLP(torch.nn.Module):\n",
    "    def __init__(self, num_features, num_classes):\n",
    "        super().__init__()\n",
    "\n",
    "        self.all_layers = torch.nn.Sequential(\n",
    "            # 1st hidden layer\n",
    "            torch.nn.Linear(num_features, 100),\n",
    "            torch.nn.BatchNorm1d(100),\n",
    "            torch.nn.ReLU(),\n",
    "            \n",
    "            # 2nd hidden layer\n",
    "            torch.nn.Linear(100, 50),\n",
    "            torch.nn.BatchNorm1d(50),\n",
    "            torch.nn.ReLU(),\n",
    "            \n",
    "            # output layer\n",
    "            torch.nn.Linear(50, num_classes),\n",
    "        )\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = torch.flatten(x, start_dim=1)\n",
    "        logits = self.all_layers(x)\n",
    "        return logits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "59a6a00d",
   "metadata": {},
   "outputs": [],
   "source": [
    "class LightningModel(L.LightningModule):\n",
    "    def __init__(self, model, learning_rate, cosine_t_max):\n",
    "        super().__init__()\n",
    "\n",
    "        self.learning_rate = learning_rate\n",
    "        self.cosine_t_max = cosine_t_max\n",
    "        self.model = model\n",
    "\n",
    "        self.save_hyperparameters(ignore=[\"model\"])\n",
    "\n",
    "        self.train_acc = torchmetrics.Accuracy()\n",
    "        self.val_acc = torchmetrics.Accuracy()\n",
    "        self.test_acc = torchmetrics.Accuracy()\n",
    "\n",
    "    def forward(self, x):\n",
    "        return self.model(x)\n",
    "\n",
    "    def _shared_step(self, batch):\n",
    "        features, true_labels = batch\n",
    "        logits = self(features)\n",
    "\n",
    "        loss = F.cross_entropy(logits, true_labels)\n",
    "        predicted_labels = torch.argmax(logits, dim=1)\n",
    "        return loss, true_labels, predicted_labels\n",
    "\n",
    "    def training_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "\n",
    "        self.log(\"train_loss\", loss)\n",
    "        self.train_acc(predicted_labels, true_labels)\n",
    "        self.log(\n",
    "            \"train_acc\", self.train_acc, prog_bar=True, on_epoch=True, on_step=False\n",
    "        )\n",
    "        return loss\n",
    "\n",
    "    def validation_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "\n",
    "        self.log(\"val_loss\", loss, prog_bar=True)\n",
    "        self.val_acc(predicted_labels, true_labels)\n",
    "        self.log(\"val_acc\", self.val_acc, prog_bar=True)\n",
    "\n",
    "    def test_step(self, batch, batch_idx):\n",
    "        loss, true_labels, predicted_labels = self._shared_step(batch)\n",
    "        self.test_acc(predicted_labels, true_labels)\n",
    "        self.log(\"test_acc\", self.test_acc)\n",
    "\n",
    "    def configure_optimizers(self):\n",
    "        opt = torch.optim.SGD(self.parameters(), lr=self.learning_rate)\n",
    "        sch = torch.optim.lr_scheduler.CosineAnnealingLR(opt, T_max=self.cosine_t_max)\n",
    "\n",
    "\n",
    "        return {\n",
    "            \"optimizer\": opt,\n",
    "            \"lr_scheduler\": {\n",
    "                \"scheduler\": sch,\n",
    "                \"monitor\": \"train_loss\",\n",
    "                \"interval\": \"epoch\", # step means \"batch\" here, default: epoch\n",
    "                \"frequency\": 1, # default\n",
    "            },\n",
    "        }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1dc4f4f7-53f1-4615-9d9c-41c86cb919da",
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightning.pytorch.callbacks import ModelCheckpoint\n",
    "\n",
    "callbacks = [\n",
    "    ModelCheckpoint(save_top_k=1, mode=\"max\", monitor=\"val_acc\", save_last=True)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e3e70623",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Global seed set to 123\n",
      "GPU available: True (mps), used: False\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "11270acb0bc34d609f12ca40e333e319",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Finding best initial lr:   0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`Trainer.fit` stopped: `max_steps=100` reached.\n",
      "Learning rate set to 0.15848931924611143\n",
      "Restoring states from the checkpoint path at /Users/sebastianraschka/Desktop/cosine/.lr_find_385aeead-739d-43d6-bfb8-66cbc716c9f6.ckpt\n"
     ]
    }
   ],
   "source": [
    "%%capture --no-display\n",
    "\n",
    "L.seed_everything(123)\n",
    "dm = CustomDataModule()\n",
    "\n",
    "pytorch_model = PyTorchMLP(num_features=100, num_classes=2)\n",
    "lightning_model = LightningModel(model=pytorch_model, learning_rate=0.1, cosine_t_max=num_epochs)\n",
    "\n",
    "trainer = L.Trainer(\n",
    "    max_epochs=num_epochs,\n",
    "    auto_lr_find=True,\n",
    "    accelerator=\"cpu\",\n",
    "    devices=\"auto\",\n",
    "    logger=CSVLogger(save_dir=\"logs/\", name=\"my-model\"),\n",
    "    deterministic=True,\n",
    "    callbacks=callbacks\n",
    ")\n",
    "\n",
    "results = trainer.tune(model=lightning_model, datamodule=dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "0542570a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/cb/1y0v6fzx5c54sztp5nqq39jc0000gn/T/ipykernel_9109/735961897.py:3: UserWarning: Matplotlib is currently using module://matplotlib_inline.backend_inline, which is a non-GUI backend, so cannot show the figure.\n",
      "  fig.show()\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = results[\"lr_find\"].plot(suggest=True)\n",
    "# fig.savefig(\"lr_suggest.pdf\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e9293189",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.15848931924611143\n"
     ]
    }
   ],
   "source": [
    "# get suggestion\n",
    "new_lr = results[\"lr_find\"].suggestion()\n",
    "print(new_lr)\n",
    "\n",
    "# update hparams of the model\n",
    "lightning_model.hparams.learning_rate = new_lr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb1581b4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "  | Name      | Type       | Params\n",
      "-----------------------------------------\n",
      "0 | model     | PyTorchMLP | 15.6 K\n",
      "1 | train_acc | Accuracy   | 0     \n",
      "2 | val_acc   | Accuracy   | 0     \n",
      "3 | test_acc  | Accuracy   | 0     \n",
      "-----------------------------------------\n",
      "15.6 K    Trainable params\n",
      "0         Non-trainable params\n",
      "15.6 K    Total params\n",
      "0.062     Total estimated model params size (MB)\n"
     ]
    },
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       "version_major": 2,
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      "text/plain": [
       "Sanity Checking: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
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    },
    {
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       "model_id": "bdac11df34f640bd90bc587ebf622c51",
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      },
      "text/plain": [
       "Training: 0it [00:00, ?it/s]"
      ]
     },
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    },
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       "Validation: 0it [00:00, ?it/s]"
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       "Validation: 0it [00:00, ?it/s]"
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       "Validation: 0it [00:00, ?it/s]"
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       "Validation: 0it [00:00, ?it/s]"
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    {
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       "Validation: 0it [00:00, ?it/s]"
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    {
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      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
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     },
     "metadata": {},
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    {
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      "application/vnd.jupyter.widget-view+json": {
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      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
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      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ab69f9fbce44ebc81223f61a74ba591",
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      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c69c118d739340bca6a28cb70cfac54e",
       "version_major": 2,
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      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f552e1afd1524365b45c2ef9eb172b54",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "721b1f85a6e3498e8a5ce9f53ac36abc",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b0de1bc6bb0a45249b5e4af5179bacf6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4efb7d9587b24038a73e05a79fe093b1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "44e883100cac4b4d95b0735daf6b8e9c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Validation: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trainer.fit(model=lightning_model, datamodule=dm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4c6fa764",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IIYQoJwwGA2fP5u+vVLt2bf7++2+nbY8//rjT7eI0iU2cOJGJEyc6bRs1apTT7VtvvZV169YV+Hi9Xs9LL73ESy+9VOTnLG2SARJCCCFEpSMBkBBCCFGJzJs3D19f3wJ/bHP5VAbSBCaEEEJUIoMHD6ZDhw4F3mc0Gku5NK4jAZAQQghRifj5+eHn5+fqYricNIEJIYQQotKRAEgIIUSlc71z5AjX04qxiOzVSBOYEEKISsPd3R29Xs/Zs2epUqUK7u7u6HQ6VxerQBaLhZycHLKysuwzMlc0xa2jpmmcP38enU53w/2VJAASQghRaej1eqKiooiPjy9wPp2yRNM0Ll++jJeXV5kN0m7U9dRRp9NRvXp1DAbDDT23BEBCCCEqFXd3d2rWrElubi5ms9nVxSmUyWRi9erVdOvWrcKOzrqeOhqNxhsOfkACICGEEJWQrQmlLAcWBoOB3NxcPD09y3Q5b4Qr61gxGxWFEEIIIa5CAiAhhBBCVDouD4BmzJhBVFQUnp6eREdHs2bNmqvu/+mnn9K4cWO8vLxo2LAh33zzjdP9c+fORafT5fvJysq6mdUQQgghRDni0j5ACxcuZMKECcyYMYMuXbowa9Ys+vfvz759+6hZs2a+/WfOnMnkyZP54osvaNeuHZs3b+bhhx8mKCiIQYMG2ffz9/fn4MGDTo/19PS86fURQgghRPng0gBo6tSpjBkzhrFjxwIwbdo0li1bxsyZM3n77bfz7f/tt9/y6KOPMnz4cADq1KnDxo0beffdd50CIJ1OR3h4eOlUQgghhBDljssCoJycHLZt28aLL77otL1Pnz6sX7++wMdkZ2fny+R4eXmxefNmTCaTvQd5eno6tWrVwmw206pVK9544w1at25daFmys7PJzs62305NTQXU8DyTyXRd9SuM7XglfdyyoqLXD6SOFUFFrx9IHSuCil4/KPk6Fuc4Oq2k5pQuprNnz1KtWjXWrVtH586d7dvfeustvv7663xNWAD/+te/+Oqrr/jtt99o06YN27ZtY+DAgSQmJnL27FkiIiLYuHEjR44coXnz5qSmpvLRRx+xdOlSYmNjqV+/foFlee2115gyZUq+7fPnz8fb27vkKi2EEEKImyYzM5MRI0aQkpKCv7//Vfd1+TxAV878qGlaobNBvvLKKyQkJNCxY0c0TSMsLIzRo0fz3nvv2SdF6tixIx07drQ/pkuXLrRp04ZPPvmEjz/+uMDjTp48mUmTJtlvp6amUqNGDfr06XPNF7C4TCYTMTEx9O7du0LO61DR6wdSx4qgotcPpI4VQUWvH5R8HW0tOEXhsgAoNDQUg8FAQkKC0/bExETCwsIKfIyXlxdz5sxh1qxZnDt3joiICD7//HP8/PwIDQ0t8DF6vZ527dpx+PDhQsvi4eGBh4dHvu03c5Kssj4B142q6PUDqWNFUNHrB1LHiqCi1w9Kro7FOYbLhsG7u7sTHR1NTEyM0/aYmBinJrGCGI1G+zogCxYs4Pbbby90ETVN09i5cycRERElVnYhhBBClG8ubQKbNGkSo0aNom3btnTq1InPP/+cuLg4xo0bB6imqTNnztjn+jl06BCbN2+mQ4cOXLp0ialTp7Jnzx6+/vpr+zGnTJlCx44dqV+/PqmpqXz88cfs3LmTTz/91CV1FEIIIUTZ49IAaPjw4SQlJfH6668THx9Ps2bNWLp0KbVq1QIgPj6euLg4+/5ms5kPPviAgwcPYjQa6dGjB+vXr6d27dr2fZKTk3nkkUdISEggICCA1q1bs3r1atq3b1/a1RNCCCFEGeXyTtDjx49n/PjxBd43d+5cp9uNGzdmx44dVz3ehx9+yIcfflhSxRNCCCFEBeTypTCEEEIIIUqbBEBCCCGEqHQkABJCCCFEpSMBkBBCCCEqHQmAhBBCCFHpSAAkhBBCiEpHAiAhhBBCVDoSAAkhhBCi0pEASAghhBCVjgRAQgghhKh0JAASQgghRKUjAZAQQgghKh0JgIQQQghR6UgAJIQQQohKRwIgIYQQQlQ6EgAJIYQQotKRAEgIIYQQlY4EQEIIIYSodCQAEkIIIUSlIwGQEEIIISodCYCEEEIIUelIACSEEEKISkcCICGEEEJUOhIACSGEEKLSkQBICCGEEJWOBEBCCCGEqHQkABJCCCEqkIzsXC6kZ6NpmquLQpbJzL8W7+aumes5m3zZ1cVx4ubqAgghhBDi+qVmmfD3NAKQkmmi19RVXEjPxt/TjdY1g/h0ZBt8Pa59udc0DZ1OV2LlupSRw8PfbGXryUsATFy4k/kPd8SgL7nnuBESAAkhhBDlkKZpvPTLHuZvimP6iNbc3iKShVvjuJCeDUBqVi6rDp3nj93x3N22htPjlu1N4EhiOuEBXmTm5PL7rni2nbzE073q82Sv+gU+X5bJzHcbT9K/eQTVAr0KLdPyfedYse8cKw+e50J6Nn6ebpgtGpuOX+SzVUfpWCeYH7eepm4VX0Z3qlHgcUqDBEBCCCFEOfTRX4eZvykOgLeXHqBXozC+2XASgNeHNOVkUiaz1x7nn4Pn7QFQWpaJyT/v5rdd8QUe84OYQ3gY9TzSrW6++z5ffYypMYf4fnMcvz3ZFS93A4mpWSRfNtEgzA+A7zae5JVf99ofUz3Iizmj2xF7KpnnftrF+8sO2u+rEezFAx2ql8yLcR0kABJCCCFugpxcC0tiz3LiQgbn07Lp1yycHo2qFrr/+bRsAr2NGA3X7p67cEsc01YcBsDb3cCZ5MuM+24bpy9dJtDbyN3RNTiQkMrstcdZfeg8JrOF1Msm7v5sA8cuZOCm19GvWTjJmSZyLRZ6NqpKWlYun/x9hLeWHsDP08h97Wvan0/TNH7deQaAo+czeOP3ffRrGs74edvJyMll9oNtia4ZzAcxhwC4q011hrSKpH1UMJ5GA/Wr+rL68AX+F3sWL6OBAc0juLttdUqwxa3YJAASQgghSoCt07FOp0PTNCYs3MHS3Qn2+xfvPMPPj3WmWbWAfI/dEXeJ+77YSBU/D75+qD11qviy50wqaxJ03JZrwWh07Dtv00le/mUPAI/3qEv1IG8m/7ybVYfOAzC8XQ283A20qB5IsI87FzNy2HriEisPJnLsQgbh/p58OrIN0bWC8pUj16Ix85+jvPLLHhqG+9Gmptpnf3waR89nYDToyLVozN8Ux8ItpzBbVJ0n/RBLt/pVSM400SDMl3fvao5bnkBOp9Mx9Z6W3Ne+Bi2qB9r7JJlMpht5yW+IjAITQghRIeSaLaRk3vgFVdM0zqdlX3WfbScv8eyPsfyw9RSJqVnMXXecW95dyaDpazl9KZMlsWdZujsBN72OkR1q0r52MDm5FsZ9t43kzJx85f7X4j1kmSycuniZYZ9tYNIPO7lz1kZ+Om5gxqpj9n1nrTrKS4v3oGnwQKdaPNunIXdHV6dOqA8Aeh2M6lgLAINeR/cGVQD4decZ5m1UzWNv3dmswOAH4Pm+DRnYPIJci8aT83dwKUOV9X+7zgLQq1EYj3StA4DZojGkVSQtqweQnGliSaza5+WBTZyCHxujQU/nuqFF6pBdGspGKYQQQogb9PTCnazYd47vH+loz1xcaeOxJFbsO8eTPesT4G3Md7/JbGH8vO3E7DvHZ/dH069ZeL59/jmYyKPfbiM718JP20473Xcm+TJDP12PyWwB4Mme9Xn6tvqkXDYx6JO1xF3M5Mnvd/DZ/dH4WAOBuetPsD8+lQAvIzWCvdhzJpWft5+xH/ObjXE8cms9tsdd4u0/DgAwvntdnuvbEJ1Oh5tBx4v9G/HIt9sY2qoa1YO87Y/t3qgqP+84w4ItpwBoFO5Hj4aFN8PpdDreuas5e8+mcCIpkwkLdzJrVDT/swY3g1pG0rtJGOggwt+TBzvX5vSlywz8eA2pWbl0b1iFbtagq6yTDJAQQogSpWkaP207zd8HzpXaXDSpWSaW7UkgO9fCK7/ssTfNXLnP4/O28+Xa4zz8zVayTGan+80WjYkLdxKz7xwAb/+x3x7IACSmZjHb+tjsXAvRtYJoEOYLQLVAL169vQmNwv24kJ5NymUTzasFML6H6kwc4GXks/uj8TTqWXP4AoOmr2XTsST+F3uWD639Zl7s34gFj3RiYIsIomsF8d3/tSXcSyMtK5cZK4/w0s+7AXiwUy2e79fIach6n6bhrHm+B2/f1dypTrfWr0LeUeePda97zaHufp5GPh3ZBnc3PasOnaf3h6s4feky3u4Gejaqirubnsn9GzO6SxQ6nY4awd58/kBbBjaP4I0hza567LJEMkBCCCFK1NojF3j2x1gAGkf4c2+7GlT186BakBfNqwVc8wJ8Jvkyby3dT6c6IYxoXxN9niu42aJxJDGd+lV9nR6z7vAFcq1Bz96zqSzccooRHWo67fPJX4dJsjbpbD5xkWd+iOWT+1qj16s+Oy//soffdsVjNOjwMho4mZTJD1tPcVvjMCb9sJN1R5Lsx7q9RQRT72mFu5ueC+nZBHoZcTPoubttdZ79MZY9Z1KZek9Lpw7NTSL9+W5MB56Yv4Nj5zMY/vlG+31tagYyvG0N9Hodn45oA6j+MX2rW/j6sIFZq1UzWI1gL17o36jA161GsHe+bQHeRqJrBbHlxCVqBnszsHnEVV97m6aRAXw1uh1Pfb+DUxfVBIa9m4Th5W4ocP+OdULoWCekSMcuKyQAEkIIUah/Diay+3QKj/eo5xSIXM2W4xftf++PT+XfSxzDotvWCuL5fo1oHxVs3xaXlMllk5mG4X5omsZzP8ay/mgSv++KZ/GOM7xzZ3Pqh/lxOcfMI99uZc3hC9zaoArv3dnUfoy/DyQCEBngydmULN5fdoAwfw98PNyoE+pDRo6ZuetPAKrj8Oerj/H77nhCfN2ZMrgpP2w9xfeb49Dr4KN7W3MuNYsp/9vHtBWH+fTvI5xNyQKgZY1ABrWI4KEuUfYJ/UJ9Pezl8PM0MmtU20InFWxbO5jfn7qFFxbtZvXh89Sv6ku72sGM71G3wNe3VYjGmkveHLuQCcDbd7TA2714l+5RnWqz+0wK/xrQqMC+OYXpUi+U35/qylMLdrDlxEWnUWEVgQRAQghRSVksGhZNK/SimJNr4ekFO1VzTvUAul+l70heO04lA/Bc34aYLRq7TqeQnJnD7jMpbD15iXtmbaBljUCGtopkR1yyvYPtf4Y2x8NNz/qjSXi46XHT69h28hL9PlrD/R1qcuhcOhuOqSzMqkPnGTJjAyNqqXr8Yx0B9dadzXlr6X4OnUtnzNdb7WXyMhowmTW6N6zCc30b0SDMjwkLd/LNhpOkXDbx5x41WuuZPg0Z0DyC7FwzX645zhnr8g11q/jw5YPtiLJ2Nr6Wq2W5Qnw9+PLBwoOkvPQ6mHRbfZ5YEMv9HWtyS/3QIj1/XoNbRjK4ZWSxHwcQHuDJwkc6kpqVS4BX/j5T5ZkEQEIIUUk9+NVmDiaksWxCN4J83PPdv+FYEimX1aiqTccv5guAziRf5tC5NLJyzAT5uNOxTggWi8bOuGQAujesQtNIx5Dvc6lZfPzXYRZuOUXsqWRirYGSzb8W78bLqJpYJtzWgCGtIvn3kr3E7DvH19YJ/nw93Hh1UBM+W3WUY+cz+OKAgSZHLnA+LRsfdwOd6obwwd2teGvpflKzTGRk53LyosowGQ06Xh7YBIAhraqRbbLw/KJd/LrzrL28j92q+ux4uBl4aWBjnpi/nfZRwcy6v22BnaZvRFGXnejbNIytL99GSAHnqDTodLoKF/yABEBCCFGhFHU9p4SULNYcvgDAyoOJ3Nkm/4y8f+x2zBact1kLVIfgfh+uJi07177tuzEdCPP3IC07Fy+jgYbW2YFtwvw9+c8dzZnYuwG/7DjDsr0JhPl78lj3uvy2K56Z/xzlsslMo3A/xnaNwmjQ88UDbVl35AJvLd3PudRsPn8gmjY1gxjQPII7Pl3L4cQMnlq4C1BNNh5uBppXD+D7Rzranzcty0TsqRRCfN2pl6fv0D3tamCyWHhp8R4iAzyZek8rp2aoAc0j2Ppyb4K8jSW6Rtb1yNvMJkqGBEBCCFHOaZrGb7vi+XXnWVYfOk+/ZuF8MOzqo3E2HnN06F196Hy+ACjXbGHZXsckfrGnk8kymfG0Zmg++fsIadm5hPq642k0cPrSZRZuPUXXeqqJpkX1gEKb1kJ9PRjbtQ5jrfPJgOp0G+rrwf9iz/KfO5o5dR629UWxWDR7gOLr4caHd7dg6Iz1ZOao0Vw9C5ll2c/TWGjT0cgOtehYJ4Qqfh72BUXzCnZR1kXcfBIACSFEOTdn3Qne+G2f/faS2LPc27baVR/jFAAdvuAUXIBq8rqUaSLIW41uOp+Wzc5TyXSsE0JcUibfb1ZrUE0f0QYfdzcGTV/L8r0JWKzD3lsXMg/P1Yy5JYoxt0QVev+VnYQbhvsxpJaFRSdUUFbUPkpXqlvF99o7iQpH5gESQohybuEWFYzcHV2dgS3UMOepKw5ztSl4NuQJgC5m5LD3bKrT/X/sUc1ffZuG08E6YmuztRlsasxBci0a3RpUoWOdEJpV86d+VV+ycy38bl1ks3XNwBKp27V0DdeY0Kserw9pSniAZ6k8p6gYJAASQohy7EhiGofOpds7+L48sDHubnq2nkzmQErB/VbOJl/mZFImeh10ss7dsvrwefv959Oy+XOPmgywX7Nw+5D1zccvsj3uEr9aZwV+vm9DQHWSvbIJrXWNwBKtZ2F0Oni8ex0e6FS7VJ5PVBwSAAkhRAnQNI21hy/wf3O3MOKLjWw7efHaDyoBtsU2u9QLJcDbSESAl30tqB+P6Xn7j4Ms2naa3DwzGtuav5pXC2CANWO06tB5NE3jx62nuG3qKi6kZxPq60HnuqH2AGjbyUs8+u02NA2Gtop0WtRzaOtI+8re1QK9qOov2RhRtkkfICGEuEHn07IZ+/UWYk+n2Letn7mBQS0jeefO5vY1nwpitmj2CfUK8vP208xadYxn+zZUazBZHwNqscul1pFaA/LM8PtY97os2BJHUraZOetPAifZfSaF1wariQNtAVDHuiHcWl+t27T95CXunLmeHdYh7M2q+fP+sJa4u+lpUNWPAC8jKZdNasLCMD/evMN5yYWIAC9uqRfKmsMXSq35S4gbIRkgIYS4ATm5FsbP20bs6RS83Q2M7lyb4W1roNPB/2LP8u6fBwp97Cd/Habhy3+w+tD5Au//a/85nv0xloPn0nh8/na2nrjIlhMX6fbeSrq9t5IFm+M4kJCGm15HH2twBGqU1cKx7bmjtpmR7WsAasHNX3eqBTZt/X861gmhZog3UaE+5Fo0dsQl4+1u4MX+jfhlfBcaR/gDqvNxu9qqU3OwjztfPti2wBW9J/VuQIvqAYzuXLv4L6QQpUwyQEIIcRWnLmby5u/76NcsnDta558r543f9rHlxCX8PNz45Yku9hFF/ZqH89BXW/hu40nuaVuDppH+LN93jmqBXjSrFsCeMylM++swZovGB8sP0rV+qH2uGU3T2HA0iSfm78CiQYiPO0kZOYz+aguXTWZ7BuhF6+KYneuFEujtPFy7Ybgf3SM0BgxoTKCPO5+uPMqLi3Yz85+jnLp4GYNeR7vaqmlrVMdavLV0P3e0rsazfRsSVkDz1cNd65CZY+aZPg0LXHMK1MivJU/ccp2vtBClSwIgIYQoRFxSJvd9sZEzyZfZdPwiA5pH4OHmWAxySexZvt14Ep0Opt3bymk4dY+GVRnUMpL/xZ7lpcW7CfJx55+D53HT63jrjuZ8t+mkPZCJPZ3CpuMX6RAVzJdrjjN/cxzHL2QA0LV+KJ+ObMMDszez0zpz8pBWkXi6GVi49RQAA5uHX7Uek3o3JPZUCmuPXOBAQhoAw9vVsGdxHupSm4e61L7qZH8d6oQwv5wtdinE1UgAJIQQeXyx+hi/7TpLVX9Pdp9OISFVLYKZnGlixb5E+zDzLJOZd/9QzVtP9KhHr8Zh+Y710oDG/L3/nL1vkE4HuRaN5xepmYv9PN3oUjeUP/cm8MXqY6w8mMisVWrVbw83PQOaR/DG0Gb4ergxZ3Q7Plh+kNY1g7irTTV0Oh23NQlje9wlhra++pw/Br2OT0e24buNJ6kZ7E2nuiFOMwu7epZjIVzB5X2AZsyYQVRUFJ6enkRHR7NmzZqr7v/pp5/SuHFjvLy8aNiwId98802+fRYtWkSTJk3w8PCgSZMmLF68+GYVXwhRxvy8/TS3TV3FqNmb+Peve5i77jirD50nPc+SDTZmi8Yfu+M5a13wctOxJP6zdD+xp1OI2XeOhNQs6lbx4T5rPxpbxgXg2w0nOZN8mYgATx7vUa/AsoQHePKcdah4wzA//ni6K4/3qGu//8X+jXihfyN0OvjrgCP4mdy/Edte6c2Hw1vZszTBPu78547mDIuubg9YejcJ44V+jZyyUoUJ8DLyeI96DGoZKcsqCIGLM0ALFy5kwoQJzJgxgy5dujBr1iz69+/Pvn37qFmzZr79Z86cyeTJk/niiy9o164dmzdv5uGHHyYoKIhBgwYBsGHDBoYPH84bb7zBHXfcweLFi7nnnntYu3YtHTp0KO0qCiFKkcls4e0/DnA+LZsjien2ta4A6lX15c+nuzotzzB95VGm/3OMIG8jn45sw2Rrn5oBzcPpVDeUXLOFoa2qkZpl4vvNp1hz+Dxnky/j4+HG9JVHAJjYu4F9eYiCjO4Sxa0Nq1It0At3Nz2Nwv1pVSOIhNQs7mtXE721A/OyvWrenRf6NeLRW+sWejwhRMlwaQA0depUxowZw9ixYwGYNm0ay5YtY+bMmbz99tv59v/222959NFHGT58OAB16tRh48aNvPvuu/YAaNq0afTu3ZvJkycDMHnyZFatWsW0adP4/vvvS6lmQghXiNl3jvNpav6a5/s25OiFdI6fz2DdkQscSUznl51nGRatOjInZMKszccBuJRpYsQXmwCICPDknbtaOK0LpVY6D2bjsYt88vdhzqdlk3LZRIMwX+4qYBHRK0WF+jjd7t3EublsYu8G7DmTyl1tqjHu1joIIW4+lwVAOTk5bNu2jRdffNFpe58+fVi/fn2Bj8nOzsbT03l0gpeXF5s3b8ZkMmE0GtmwYQMTJ0502qdv375Mmzat0LJkZ2eTnZ1tv52aqqaEN5lMmEym4lTrmmzHK+njlhUVvX4gdSwLNE1jX3wadav4OGVfvttwAoC7oyO5o5WjY/AXa4/z3rLDfPzXIQY2rYLZnMvCYwZMZo1u9UPQNFhzRA0Nf2NwY7wM+es+rHUkG49d5PvNqhlMp4Pn+9THYs7FYnbsp986GzISsXR7AXRF62VQN8SLf57pCkBubv6muutR1s9hSajodazo9YOSr2NxjuOyAOjChQuYzWbCwpy/CYWFhZGQkFDgY/r27cuXX37J0KFDadOmDdu2bWPOnDmYTCYuXLhAREQECQkJxTomwNtvv82UKVPybV++fDne3gUP97xRMTExN+W4ZUVFrx9IHV3p77M6fj1pIMCo0beGhY5VNJKyYf0xN3RoVE07zNKlh+37h5rBx81A3MXL/GvuMpKydBxL0+Ou1+jhdw5/I/hn6/AzQsaRLSw9kv85NTMEexhIzoGWwRq3Rljy7euTlcBt+18AYNsZE/GBbW/2S3FNZfUclqSKXseKXj8ouTpmZmYWeV+XjwK7cvSBpmmFjkh45ZVXSEhIoGPHjmiaRlhYGKNHj+a9997DYHB8CyzOMUE1k02aNMl+OzU1lRo1atCnTx/8/f2vp1qFMplMxMTE0Lt3b4xG47UfUM5U9PpBOavjxWPoUk6hRd1arIcVtY4Wi8bKQ+c5m5xF00h/Gof74eWuPouHzqXx5doTRAZ6Mf7WOri7FS0bcvJiJnPXn6Rf0zD7Ipx5ZZvMvDF1DZBDiknHD8cM/HXOnTB/DyCNWxtU4f472uR73IUglQVafMLxv+LZPg24v4tafXxwEcp2W59cLBYNf6+CXxN9zEv2v9tlriT3vlfARSOsytX79DpV9DpW9PpBydfR1oJTFC4LgEJDQzEYDPkyM4mJifkyODZeXl7MmTOHWbNmce7cOSIiIvj888/x8/MjNDQUgPDw8GIdE8DDwwMPj/yjIoxG4017093MY5cFFb1+UE7q+NODcH4/PLEVQusX++FXq+OyvQl8sPwgh86l27cZ9DoahPkR5u9hXVtKbV939CLTR7SmepDKqKZn5/L7rrNE1wqmXlXH3Dlmi8bEH3az+0wK3206RZ8mYbxyexOnifcW70zgQnoO4f6ePNKtDjP+OcqF9GySMnIAeKBz7QLLPLpLHeasi+NCejb1q/pwa1AqD3WJKvwcpsbDps+g85Pgo/6/BF3tfOdkQOwC9bdOj+7cbozH/4aG/Qp/TCkoF+/TG1TR61jR6wclV8fiHMNlw+Dd3d2Jjo7Ol/aKiYmhc+fOV32s0WikevXqGAwGFixYwO23345er6rSqVOnfMdcvnz5NY8phMuc3gaz+8LprSV73KwUFfwAXDxW7IebNXjku+3c+/kGMq4YQm5bFPPQuXT8PN24tUEVQn09MFs09sen8s/BRDRNo2ejqvh7urHzVDJ9P1zNCz/tYvba43R//x9eWLSbAR+v4fPVR+0TAs7fHMfuMyl4GvUY9DqW7zvHHTPWc/S8CrI0TePLtaouD3Wpzf/dEsWGyT2Z+1A7hretwdhbori1QdX8lbFY8HbT8eO4Tsx9qB3/e7wzzYO1q78Af02BddNUEFQUu36A7BQIrgOdHlfbVr+HPQoUJU/T5PUV182lTWCTJk1i1KhRtG3blk6dOvH5558TFxfHuHHjANU0debMGftcP4cOHWLz5s106NCBS5cuMXXqVPbs2cPXX39tP+bTTz9Nt27dePfddxkyZAi//vorK1asYO3atS6poyinslLh4lGIbH3zn2v5y3BqI2z9CqqXYJ+Rc3sdf6efK/bD1yXoWHlCDSN/9de9fHBPS/t931o7G9/WOIwP7mlJgJcRTdOIT8niZOw/tP9nJOfaPk/kwNs5dTGTJ7/fwc5TyU7z6Ph7upGalctbSw+wJPYsD3aqzfvWdbMm929M57ohPPn9Dg4kpDHii43MGtWWw+fSOHQuHR93A/e2V1NlGA16ujesSveGBQQ+mgY7voPlL0FYc6Ie+JWoUJ9rd5TUNDi6Uv198fi1XyxNg81fqL/bjYXm98DmL+HMNjixFqK6XvsYongS9+P2eQ+aBPcEBrq6NKIcculEiMOHD2fatGm8/vrrtGrVitWrV7N06VJq1aoFQHx8PHFxcfb9zWYzH3zwAS1btqR3795kZWWxfv16ateubd+nc+fOLFiwgK+++ooWLVowd+5cFi5cKHMAieJZ+ix83h32/+/mPk/CHoizjnpMOnz1fa/n2DbFDICSMnJYesrx7+H4jr/Z9cObkJPBxYwclu5WzcxP96pPgLU/jE6nIzLQi06XV2PQzEQemgeaRo1gb35+rDMLHunIsOjqNK8WwMsDG7P15d68d1cLfD3c2HMmled+2kVqVi5NIvwZ2aEm9cP8mDe2Aw3CfDmXms3QT9fx3E9qBuXh7Wran7dQORnw/b2w5AmVDTu5FrZ9VbQX4PwBSLc2paecvvb+h2MgcS+4eUGrEeBbBRr2V/ed3V605xTFs+dndLmXqZ20EswlPEoqOQ7WT4fcnJI9rihTXN4Jevz48YwfP77A++bOnet0u3HjxuzYseOaxxw2bBjDhg0rieKJykjT4Mhf6u+tX0HjQU536zd+SquTK8DUA260zXrLF46/L5RwAHRut+Pv9AJWG7c1HRTQSffDFYe5bNbRKtydV7wWER3/PeyDtOR1LK73PjlmCy2qB9C8egBs+BSST0Hft0CvV1kPgJQ4FUhUbYxer6NjnRA6XrGW1D3tatCzcVW+2XCSbzecIDPHzJt3NLNPVhji68G8sR0ZP28bO08lE+jtTq1g76LNlbPpMzj0JxjcoW4vOPQH/P0mNL0T3K8xuMGW/QFIOVX4fqAukn9ap/NoNwa81KrpBKvO1STHFfy4ikrTSqfj98l1ABjNmeSe3gz1upfcsRc/pgJmd29o+38ld1zhEL8LqjZxaRFcvhSGEDfk4nHIzb72fnnlZF79W33KKci0ziB8bKXqDGuTGo/+7ynUurgG/YpXil/evC5fUv1G7LcvQkZSkR+uaRoms6XwHa6WATLnwhc94ZshfLn6KGO/3kJCilrzatvJi/yw7QwGzHynn6KCHyBbM+J3dj1N14zHgxxGdqip6rDsJdg0E05tUt/E42Mdz3Poz2vWI9TXg0m9G7Bhci82Tu5Fm5pBTvdX8fPgx3GdOfRmf7a8dBs/PdaZqgWsVp7PwT/U735vw/DvIKwZZCXD329c+7HH/nH8nRZ/9QzDxhmqudSnKtz6gmN7oMpkc+lk4Y/dOgfejXJ+vuLIyYRLJwq+L/Mi7qaij4gpEbt+gPfqwIHfS/7YWamOz60py6nPnO7I8pJ7nksnVPADzu/lkpCbDXP6wew+JZ+1Kk+OrYLZveGnh1z6OkgAJMqvIyvg41bw5+TiPW7JEzCtBSTsLvh+WwYDQLPA7h8dt3f/iE5TQYdh+1zYewPrzO2cD6ZMqNoUAtRaU0VtBrNYNIbP2kjnd/5mz5mUAnYwoyXut980paoAKD07l/f+PMC6DWtU08zxVcxYupkV+xN5fP52Lmbk8PSCnWgaTAxci+/F3eAZQObdC3in6jtkaB501GJ53nMxg1pGwvHVgDWTdGwlJO6H3CxHOQ4V4cJ0fDWc2oKn0UCQj7tju6bBnp9V85LZVPhUFgd+h8QDztsyLjgukA36g8EN+r+nbm+be/ULW26O6rdjL4dFBUEFSY2H1e+rv3tPAc88maUgawCUXEgAZLHA6g9U4Pu/p9VFvbh+HA0ft4a4Tc7bs9Nxm92TnvtfhOy04h/3epzbB0ueVPXZs6hkj61p8M1g+LiNep4zW8Hs+OKjP1KC8+TELnT8neczVCI2TIe4DerLwqlN197/RiUdVf+jLFf5ogTq9Y3fpT4bl5NvbplOrFNN07lZYM7B/v/DBSQAEuWXLXtSlA+4jcUMh5apWe1szRzmXJXFOLBU3bYFQF7WOWhiv3eMNolV2ZBUT+vyB0ueUs0/1yFzyzxVpHZjHUPULxwC4PPVR5m6/CAWS8H/HGL2n2PziYucT8tmxBcbiT2VrAK6JU/C6W2cOrIbXe5l+/4p59U357eW7mfGP0dZtNSRmamtS8BNr+Ni3D7W/nc4/sn7qRnozgOWX9UOt0zEu2l/Xnz0IX6IeB6Au9034O2md85cHF3peO1CrPU5tREyLxb+IiQdhW+GqItb1hWB3NG/1DfEecPgv/Xhrzfyj/jZ/xssGKECgbyOrAA0CGsOAdaV0mt3gWZ3ARqG5ZMLHz10ZiuYMsA71JHFKShjaLGo1zsnHaq3gxb3Ot8faF3PMDmu4Oc6uRZSrce9dEJdHAty4Yh6ntSzztvP7YPDy1SAdmXfpq1z0KWexsOcju7cHm66nEx1rmzBb0kHDsdXw9kdKujZPEtdRAFLnZ5Y0KO7cKhondWvJc9nHFD1uJ5RZvuWwO/POgefKWdg9X8dt4uQHb0hKafhy17qs/Hb04X/jzz4J0xvC7O6qkC8KBnSaz3v4sdg1XvqvZvX2R0w7271xa9eb7jnG9VE7SISAInyyWJWmQFQ3zgTdjnff/AP+CQaDq9w3n7hkLpgAcTvVL8P/aEuPr+MUynqM9ZOq92eBYMHJO5Tx0/YBYn70AwerKv3IpaIVpCdCnt/zl++3Jz8F/Q8zNkZuF9UF4mY3JYQ2sBevmV7E3hr6QE+/vsIc9bl/6euaRqfWhfi9PVwIzMri1VfvoD2eQ/Y/g3mH/+Pmd+rb+DJqDl23LOSWLA5jvmbVH+UZgZHv5S7onL47P5oHjL8yWDtb753/w8L6q3APycBzStIjWoCPNwMjB7zOGajD/45iSqDlDcAOrNNZYEAmgyGKo3VxXnnPFgwEt6uoX4+aARxG9V+uxaqfUyZKjDN6/ga6x861dS25r/OQ9I1DVa9q/4+v181kdjYLi4N+jofs/cbYPRGf3oz1S8VvOSOPTCuc6sjiEk5rZ7v+xHw1UAVfGz8FI7EgJsnDPpI9X/KK6CGWgojNwvSE/M/j23OoGBrf6Y1HxQcaP3zFmz/xlFXm7z9x/YtgWzr+zonE9Z/bL9Ld74IwYimqQu07WJ/ehvM6Q+/PlG0AODPF1V/L88AdfvCofwdiHNzVGbuemz+3PH3rh/UZxbQ6vcjybeh2n64gGxjWgLM6AxLn8NpvRJQWb6PWjnOA8CpzXDpOBh9QO+mPt9XnpPcnKsH9ZkX4ZfH1Pn5bZLj9Yt5Vb3PPayvUVGyo0Wx9xeY3l6dMxtzLiwaqz43oN4/vz6ugrLp7WD9J459/5oCSUccy7YcXn79UwuknoW5t0PsfFj5H5geDT8/6jjeqvfVl4s63VWztFv++fdKkwRAomzKzVEZmcLSsae3qsDH5so+FOunqw/1ojHOGZq8zVu2ZhDbxTgrBQ78Bmd3qtt1ezpG8vw2CdZOA0Br0I8coz9avd7qvqQC1k1YeD982ExlOAqwd9sa3LBwTgvkt+M6CKkHgCnxEK/84vjG/t6fB9l71jmQWnP4ArtOp9DImMDG5kvY7vUET+kWoLOYQGfAkHKCh80qje/ZoCcA/rpM/v2zqvtdbapzb03HMYfXNXFbkzB6haj+RwG6DCL3qEDD0n4cePjZ99UZvTDYJvZb/4maX0hnAP/qKqtmGzVXLRoa9FF/L39Zva7ZqeonLV5ts1icv23v+9X5RTq1Wf0e9BHcZl2qZvkr6lskqIApb+CbuE/9NpvgyN/q7ysDoIBqKrAFmp5ZiH77XHVxSLP2kdI0R/BUp7ujaTLllLowHvxdZW4+vxVWvKbu6/c2hDUlH4MR/K3ZpyubwXIyHPUdOhNqdFQXx7//47yfpjma4w7HOC4kWSmOphp3X3VROfCbur39a8jI0+n9/BXNg1cym6zv1ybqS8OisTD7NjU6cce3zp+ZguxZpJ4TnfpG7+EPllzH5+LMNvjlcfhvPfhvA8cXl6tJT1SZifREFYActGZn/SLV62R9D1hqdeacv3V6hisDaIBtX6vReZs/h/895ciC5GarrNql4yqLa2sOj52vfjcZ4shiXpnN+u5OVY/V/1WBxpU2znB8ydr9g8rOLX8F9vykXqN7v1OfmQsHrX0Yc9TnxhbAApw/CKe2FPzanNri/H9l3TR1rGV5spqr3lVNbe5+0Ovf6nlj56ug7MIh9dnVNJWhstVv/EbQG1XG8tJ1ZNPSEuDrQeqxgTWh3m0qqNq1QH1Os9OsmVnUgAljEfrx3WQSAImyafePsOA+x0XmSoet/+zcrB8iW+YBVNAUt0H9nZWs/qHb/lHl/WeedERlDWwXWoCVb6mLibuvysrcMkH9fWarPdNjaT4cAC24rvU4VwQ5GUnqW1R2KtrGmWTm5P8neTxWZTdiLXVZdeg8ucHqn21K3F4S07KpE+pDr0ZVyTFbeOSbbYz4YiPd31/JQ19t5vXf9uFGLj94voXvnu/w11I5r/nzbO54Ujqr0UhRenVB96zXDU2vUsyhpBDgZeRf/RvifdHxT90t+QQA1UzWrFCAynqYDN5Y2j6cr+w0GaJ+7/tF/a7ezjHbsbV/lAqA8syAHNkaxsTAI/+oc3Z6C6x6R/2z1VtH0h2OcTQZ5OY4ho/X6gxdnoZGt4PFBD8+pP6Rrn7PuVy2i9ipTWpCQu8QVY4rdXoCLSgKz9xkDH88qy6E3w9XF8dj/6h/1gYPVf4Aa1NnymlHwKwzqL4Lllz1WkQ/lP85bArrCL3/N3WRDIqCGh2grzXw2fOT84i9i8ccHdhTz4CtOWvn9+p9WqUxdH5KbYv9XmUfrIG6pWYnVVxbYFgQswl++j9H8HTxqPrsaRbVqRucsy9Xungcljyt/u72rAoaqzZWtxP3qX5NXw+Bnd+poE0zqykmCurvlHlR9UH5ejB80FCdk+lt1fnRLFC7K9z6nGN/7xAIbci5AGsAdOwf9braXNmcteM7FQTlZquRi7bJQc3Z6j21/BUVDAO0vNe5HjZp5+DEGvU+/PsNmNPH+QvW5WTYNEv9Xae7+v3bREdGruszENUNrOeGw8tVn8SF98Pv1uWYLl9SHYRn90Z35orJUc9sU/d9NUB9RtLOOb4QnNqkmgqPr3b0Sxv8EXSdBHfMguC60HKE+ryln1NBeXwsoKkvMFUaQo326nF5R0EWRXqiOm9JR9SXhgd/g/sXQWPrAjOxC1RdzdmqHC4e/WUjAZBwrdycgtOttpEt1qGu+djSx7YZd09uAJO1z8vRv9U/Wv/q6tvoqY2q+QTyf5s9s9XRFAaOb62RrUFvUL8fWwe1blHb/SLQ6vRQf9uaLq7MAB1fha1jn2n7fNr/+xe+3ei4AF7OMWNMUBf33Vo9UrNyic1SF5vA7LMYyWVBxPd8njyWNZ6TmJ75HMeOHuJEUiYrD57nSGI6Xd3242+6oC4CoxbzVMT3/JR7C2P3t+SS5lhagvAW6PzUMjBV9SlMGdyUEO2ic/bs4jHVNGEb+TZmGeZ2j7Ct1qPOnXpt6t2m5ruxqdPd8c8e1Ld0v3D1T77bc9DnPzBmhfrnGtnaETDYmnRaDFeBgDnb0YyRsFs1HXkFqeyYTgeDP1H/XC8dh+/uUufSzQvaPKAeYwsObJmAer3VObySmwfmobM4E9geS4MB6lvy2R0q22G7cESPBt+qBQdAbUbBnV9Ax8dVma425NveD+iKAMiWaWh5n3p89bYqWDPnWLMpVnk7Y4PKTlnMjuav9mOhpQrIObYKPu2g5i/yr46l52sA6M4fKPgzZs6Fnx+G/UtUP4x7voU7v1RNnsPnwQhr09DexQVPo2DOVRnWnDR1rm+1TgWQN3CI26Du96kK9/8MfhHW/k6fOB8r5lXVz+t/T6vPj2ZRfbCyUtTnGaD9w2qCSQ/re7JWZ9DpSPeshqXFveoz/+NolTkC5+as26cBOnWOZ93q6IvT9y31fk06rIIUzaLOfVQ3CLNepPNmgI6vUr99w1VT1plt8PXtqvkQVPCTnaou8CMXgW0NPp+qcO/30Ms6ctSWHV31nmoGBhV4XjgCGz+zNp9r6Je96PhSYdsfTZ3jIzHqJ6+/psCih9U+bR6w9nlDvUee2g53zISIlo7Xx/b/sJp17Tzb/7bCRiXGx6rga+2Hji+VGUmqH9+Fgyrj+eD/HAMAWt7nqNsea1eBJkNctj7elSQAEq6TlqDS4r88lv8+W9v1hUP5+9KknLHOcaNTFyG/CHXxtDVl2S6Aze6AgVPV3xs+VR9U2+zI4c3V7+3fqIuOTxXnWZ9t/xAAgmqrD/WIH9Vvg8pY2DNA6eecOzvm+efhbs5gqH4tr/9vLztPJQOwfF8CTTUVNHlHtQPgzxMal3VeuOksTK29haqHF2BIPkENEmitP8KcFvuYN7YD/x7UhDtbV+PVutbRYo0HQ92ePNRVNaFtOZvLl7kDHGUJa6LqBiwYUYehras5hscbrO3vF4+plDuoC7Z/JJY+b3EuoJBZsN19oH5vx+26PdS3c1sfAttrp9NBz5eh8xNqFJZNl6ecOz62ui9PVmmJ+m0bIVOjg+OfpXewev3bjlEXR4BO4x3/tBOuCIBsF5kCaJFt2Br1BOa7v4Ee1lGEf05WAbfBXWWcAAJtTWCnHU2jEa2gxT3Q7y1Hn5fCFDQSLD5WvUd0ekfwAtD+EfV76xzHxcX2BcDfGogdWq4CpKQj6rlbDFfvz1pdAA0yElXm8r7v0cKaqg7CWcnqs5aXxaz6vO1drDICw79T/bZa3A0DP4DGt6uArKCgzGbbV+oC6hkAd33pOMdVrc2Bifsdn4V6t0G9XtD7dXV7zVRH35rT22DdRyqjFt5cNdk8tROeOQA9XlJ9cao0hoYDwcMXOqiVAmgy1F4U88Bpan4niwl+GKX6/tmyP02GQNuH4L7v1Wfh/H6VPaveHjo8Bnd9oc65TxW4d75qctXpHFmKxDwzqtsyIy2Hw2Nr1Wt/6YQKgn58SPXjAmv/QTe4dx7c8blqXmqU53Npy47avnR4BalA56/X1JQSADo9+vid1ExarW6f3enccTr2e8ft1qNUHc5sU8FRaEPod0WfMRtblufUpgICoO7q9/HV+ftMZaXAwlHqPbniNfiqH/xvgsrSJe5TQeGD/3PMfwXqnHuHqiZZW5axSVGWHS4dEgCJkhEfCzvmFe8xp7eoD1VBfQKykh1/21K8x1er0Vq/P6NuV28HPiHO31osZse3ovp91TegkHrqW9nyl9U/WZ+qqjkFHBfcGh1Uetgm8orVxPV6dUHNs6BoXKaRy+5qzpq9e3ZwICGVE+fT0azNcadCugDwgGE5JrOFx+dtZ+OxJJas300tveoUW6elyix9t+kUh8wRANx+4Uv1BK3vh57qG2OTSyvpUi+Uh7pEMXVYM6LO2zobq8ChV+MwaoWoBUO/tfQhO6y1+vbl4Qe+KgPkkWX9Z2ubILGu6h/E5UsqSwZQpRFFYgtY3H3VRdIr0PGaVWtT6MMA8I90ZG0CakLNzo7jHV6uOvHaAqDq7ZwfGxwFt0+FZw6qBV57vOwIZs/tVc2RFw6qZqq6vYpWl/aPqAuGKUPdbn2/Y+SYrQ9Q8ilHBsj2DbooCmoCs2WZmt2lLqA2TYaqjF7qGdXJV9Pso53o8S/1+/QWWGHtD9XjJUf/rFufV2Xt9AQ8uhoiWoCbJxke1kWg817ELRbVuXn3jyq4uOfr/H2lbNpZm0C3znGeaiAjSU0qCeo9asuUgSMDdG6vIwCqa/2MNr9bZYtMmappSNMcTZktR8C4tarJJjhKfdG49Xl47giMWe4IsHr8C57e5chugKrHnZ+rLwTmHDUy0DZ9RUvr6LyG/VUg0myYet1v/1B9rmvfAhP2qGM2yrOkhq0e5w+pgFTTHPWp0119WXjwN/X74jHVRG7OVv+PbMGZh58KlnycJwAltIHjvRF1q/pyBaovUFaKej9a+701if8R3ektjveNrVn34J+OgKztQ+p9C6qJ+e65ahLHgjgFQDucjxnZWmW2spKdM+OaZh3xelJ94fTwV+/FbV+pbHJATRX8hNR1fi6DUX1ZsAmsqb5AlBESAIkbp2mw4H74dTy605uvvb+N7Rtg5gVH85WNLQME6ltKbrZ6jg3T7SNA7P1ObP9cD/6h/kFlJqkPcc2O6h+cdRSTvdmhWrTjQ6hZv+XUaK/+oRrc1TfzKy+8eWSZzCw9paf/J+vZk6WyK58tWka/aWt4cOpCdMlxWPRGHk97iAzNgwb6MwwNPMaZ5Mvc+/lGck+r5q+cwDp0alYPN72OyyYzR7VIADV83eChLiztxqpv6OcPOLI0cetVHb2C1T9v1CrsD3dVTXJdmtbB47F/4A7riClfVUZ7x1hbpqRGe/WtDRzNBlUaFlpvJ40Hq7IN+K89I0bv11UTxdX6xNh0n6wuhgP/q85RZGv1z9GUqf7R580AFcTgpoJRvV41Rbp5Qe5lxyixmp1UUFYUBiP0t35b1rvBLRMd99k6MeekqX/0ereCOzwX5somsHP7rB3FddD1Wed9jZ7Q5kH194ZPVfNN6mn1nE2HqiH9aOriVLWJyoTZ1OkOE/eovkRGR/Nkqpc1MLE141gsqh9M7HwVJA6b43zRv1LTO9Q3+NQzMKMDzOikRvL8+YIqR1jz/DMl2zIn9j4mOJqCdDqVlTV4OPq/HPpTfea6XfF62HgFOTfF6nQqs3ZlM4rBCHfNhoYDVCCSk64yZ7XzrMPmEwrDZsPTsRDezLHdLyx/wBBYG4ze6liXjqtsdNpZVXZbH55Aa3+XxoNV8Pnw3zBqccFNr3npdNDvHfV5uetLqNHOOWDv9hx0fAwttAEeuWm4fd3fmkHRqU7z4c1VtisnXX2hi2gN3f+lAq+7Zjua7wpS3RoAJexRs7Wjc/w/NLg51q2zBVcWi2oy3PeLei8O/w7Gb1DnPXo0jPoFntoBVRoU/Hy2ABTKVPMXlIGlMEQFcM72QcI64iS0aI/LO7w05QyE1nPczjv668x29WHMTlFp6lYj1DeQ9o+q++v0UP+oLhxUc0wA1OvpuDC3vE/NIWP7hl+tTb5v8Vr19uAdjO7+RZCTwd/xbnz/61YahvkRXTuIrvVCcTPo0TSNsd9uZ9NpPWAhNbAWZB2ipU8SGzR3bs1W37Q359ZjV6Y3f3jdyjBtOa9V384W1D/c/oYzkAHuNdvh7mmkfVQw648mEe9W3TEnWPSDqh8NqADv8HKVrbr1OcfooUYDHXUERnaoSZ1QH1rUCHR+na0ZIHtnWltfmfDmKnhIT1Df5kB98ywKN3fVVJJX7S7qpyh8QtU/fhudTgVQP46GtdZmS53h2tkkUBebsCYqULZ1Yr1K81eB6vaAu79WF1pb0ALqougdogJOUFmB4gzdtTWBpZxW2Unbt/gmQ6BqAdm2tv/nmCxvnvWbc2Rr1ezYoK8je9f/PedmxUKkeVYHtjjms/l9kuoHo9Orph9b5q0wRk8Y+SP8847qi5O4z7lTcP9381/sfULUey79HKCpJjFrPzRAnat+b6lM7o7v1LZmw/JnD66Hm7vKfiwcpQZKtHkg//QERaXXq4zo2e0qm2X7/NTs6BRkElQLhn9b/OM3GuDcLNb9RfUFLrQBNLsT9AZy75lPwvdPUj1jF7qcDJVNqdJQ/U+zdfqv30eV1beKyuZdS0A1lS20LfFSpaFzgFmnuwq2Nn+uOsmfXKc6fgP0etWxYPPtHxatnuEtoFpblclvfs+19y9FkgESNy7P8FNdcYZP5l1j6cr1lpwyQNsdF/1md6kLZbdnVX8AUB/8+xeplLIto1M/T0rfK9A5DVutDfhH2AMDs86N1rPPM+mHWIjqRk7dvry4aDcx+84xfeURHvpqC28tVen//fFpbDp+CYNO4+PhLejZWX0THNvYwtaXe/NyI9XXYq3Z+u2y9UgAAk/8ybqJ7Vj3Yk/ujbRmYqxp51Eda+Gm19G6tfWbmcEdukxwlNfeP+ZXlYq3jXTJ0wcC1GKkneuF4utxxYXRNpon/ZzKtNk6bYc1y9Neb428itoEdjM0vUN9o7QJb64u/EURZn29bRPx5T3/RX7+oY5mwbzyNu8Up/kLVHOB3qiaXg/HOGYO7/ZcwfsH1lBNOTqDY1bwWtagsuW9qsN29ENFXl3ekQHap77Fb/sK0KlRQXmbkK6mWhsY+QM8dxgGT1eZCp1BlaOwgNfWfATOHeRt2o5xjBBCV3j253q4eai+PGNiVHPajbBls+I2Ojpj2zLOJa1Ge3hsPYz+3RFUBtVme+3HyJ1wAP5vOQyyjiZrNkydAyh+sG97Lpsrm/sbDlAZ9PRzaqTmiTXqC+aA/zpGHBaHTqeC6PEbVdNsGSIZIHHj8kxAprt4HLyvaD7aNEt18Ot4RWdnpwzQFZON5e0DlHbWceEo7Btrrc5qtNbf/1EXjisWMKX9w7DtKzSdng/3+jDn22V8SiS36s6xy1yb5BwDi3ecYUSHmpxMyiQxLZtQXw861Anm913x/LD1FM/2bcCSWDUbb9Mgjf7NwtEdtmatko6AxYz7KTVqJ6xVXwaaIujXpzmcrK/KtG+Jyl7ZOx6qAKh/8wgONQ1Hn5sJGStUx0FbHxRQ/5B0BvXt/8ueKmPjGaBGqhSFry0AOq8uhLYRNn7hzh0WofA0dmnp+7Za1uH8fkczQ1HY+gGBCoSL2pRXFAE18vT/aVW8x+oNKqi5eEw196CpwDVv88uVmt6hskU/P+wY/g2qye/FuGI1IdhnLE/Y46jD7R86fyEoKq8gNQKuzShVPt1Vvj9XbeLcX+ZKtlF9llx1AS7J8wUqO5b3In+9bOfJ1jEZCq5PSSkoKwgq41QzT3OwX5gaUZaw+/qC/RodHMuVXJllDagGE3eredj2L1F9inq+fGMZOu9g9VPGSAAkbkxGktM8OrpLxyFvU/rF4/CHWj6BqFud26bzzp+RNwDSNEcTmHeo6iOUe1llbArrEwKqw2H/dwq+L6wp3PkFv+w6x8cb1BDwtYbG3GrcwWG/9vQIrcLKg+d5f9lBUi+rxfn+75bajOtWlz1nUjiZlMmSnWf5nzUAahNqzZiE5AmAjv6tOjB6BjLqzjsYZWuiaHmvmjMk9nvVGTvzgvpGFea4COr1OpXtuC/PvCU23sEq2Dm2Ul3E3P1gyKcq3V8UvnkyQLZOtREt1UXINpQf1HDga41qutncvVW2Ydtcx6ioosjzWtKgb8n2M7B1hIbiZ4DA0Uk247zqq9TnzWs/pvkw8AxUHVHzZqWK2ZyT4RGG5uaJzpYZa3Gv6jB7o67Vx8WWAdIb1ZeTgngFFvx+L0ta3quCx/1L1GfXvxqEX8d74GbI21etuPIGhwXNleUZoEZntrrv+p+jHJAAqLK7cFhNBli9gA9BUdjWXPIKUs1Wl45DZJ45R/JOT79rgWMYrClLDdm1yRsAZac5mrLq9lSzqYIauXWtf7xXOJeaxbK9CaRl5XL6UmO+36OaVN4Y2ozudW/h4tnB3N20J10zLNz6/j9sPq6CI293AyPb10Kv13Ff+5q888cB3l92kKSMHHzcDTQNtA5TDrJmULJSHPPatBrh3D+jxXA1YubEGsdQ/d6vF28m1PaPqG/UUd1gyHTnfirXYusDlHFe/SMHxwzXeQOgkv4Wfr0Ca6q+BsWRt2Py9XwjvhpbE5hO7xxoFZVttA+oJpnAGoXvm1f929TPjdDpVZ+ShF1qArqB/72x4xVVne5q/p1GAx1N1eWRVxAM/VT1d4tbr0aPXW+forIkrJnq76eZr+89XUFIAFTZfT1YXRifO6w+7MVlm5G59f2w4VN0pkw8cvPM25N33opdP6g5PvQGNaokr7x9gGz9fwweJIW2JQQVAJkbDaao4c/6oxf4fPUxVh86z5Xrib7YvxGjOlovSlVUIBARAPd3qGVfe+uetjUI8FYdjIdFV+eD5Sr4AejduCruBmt53b3VSJPU046OxLZRZzaBNVSfjeOr1ciNRrfn3+daGg2Af50pep+YvGwZoJx0axl1jmkAgvI0gbmy/8+N8vRX88Mknyp602BR2ToyhzYsfGjx1diCzMBa19eH4gaZo8fgtm02DJ3htKzJTRVYE54/pkYNVQRGz4L7h5VXBiOMs3ZsLmomuQKqIO9OcV1Ml1X/GlBTmRc3ADLnOtZ2aTRI9XFJPolPtnW0RHa6YyZbN0+1BtSxf1Qflyv7/OS9bev/4xXEX5l1GKbpOE8A29LrMoCrO5iQxpu/72PN4Qv2bdG1gqhXRX0L7VAnmDtaVyvwseN71OXHrafIzrXwf10cgUGorwd9m4bz2654AG5vEU7GkTwBW0hdx6re9W4ruK281f0qAAqooTI419NEcz3BD6i5emzDxEGNYvFXcw7hFaiG01++6Pr+PzfKNpS9pNW7Tc2HY8uaFVfrUWqyvLYPuWT9I63VSGg3utSftyys9SSuwsULkZYFEgBVZnlHWuVdiK+oEnZZ+7wEqKGRwXWsAZC1aev4KjUpWVBtdRHZ8qVaEyZvABRST/Wfsa22rdM5yuUVyKI4X5aYXuScFkTAhlMMaFV488H6oxcY+/VWMnPMGA067m1Xk4e61KZOlaKl4EN9PfjliS5kmczUDHH+pn9/x1r8tiueUF93OtcNISbv6hchdR1T5NsmjrtSi3tU3Wp2vL5M243Q6VQWyDYXjX30jVXNjmoOpeJ0Oq5MjF431nTkEwKDppVYcYQQJUMCoMosM896UDlphe9XGFvn5xodVLNWcB04ttKRAbI1f9Xvq/rBbPnSuupxmiMAqt5ezd5rzoaM8xzJ9ObE9oPcBuR6BLL12CXMluYY9DrMJy+x+3QKzaurjrqrDp3nxUW7qB7kRZuaQXy1/gQ5uRY61Qnh3bta5AtiiqJuIcFSxzohfD4qmmpBXhgNV/QBsK0aHVjLeYmIvHS66xt5U1KcAqArRsgN+0r1xypOvyIhhCjnKkBvLnHd8i6IeT0ZINusz7YRBda+Dj7Z51Q2x7bERYO+aqhlSD3VDHPwD8fEicFRaq4UIDXhOPd/uYm/dqgZj8/nemG2aDQI82VQC7XPV9Y+On/tP8fDX28lPiWLLScuMWv1MXJyLfRuEsZXD7W7ruDnWvo0DadpZAGjpFreq4Y2D/6k2J20S42tI3S1tvk74Ro9JfgRQlQ6kgGqzJwyQBnFf3zeDBDY55TxzT6HLn6n6vNj9FHLNeh0KvOw9kM1caJtEcCA6uon7SzfLVtLQmojAgyqLAeSVTDRs1EY/ZqF88vOs/y84wzrjl7gYkYOJrNGv6bhdKkXwsqD56kd4sPkAY3yZ2huNu/gos3A6koRLdXsrq1GXHtfIYSoBCQAqswuF7EJLGGPaj5pOMDReTfljBq5pTM4ZhK1ZYByEtFvmqG2Nejr6GxXv68KgI6scKzTZAuATm8m6ewx3N2aUN/PBJfhaLoahdWrcVVa1QhkQPNwlu5O4FxqNgADW0QwbXgrjAY9ozrVLoEXpALr8rSaMv965rERQogKSAKgyqwonaDNufDdnWoSva7PqAU6dTpH81d4M8c8H9aVrY3mTNhnnbk572Rd1ds55guyjfQKqEGGVwQ+QKQuiZcHNqb3KU/YBymaD4HeRtrUVJ2GZ4yMJjkzh+MXMjBbNFrXDMKgLzsL65Vpbh4Q2crVpRBCiDJD+gBVZL8+Dj88qIKYgjg1gRUSAJ1c51gEcM0HalFEyN/8BWD0QvOLdNxuOABzWHNGfrmRez/fgAm9Gg1mpwP/SP5JUPNQNPVJZVTHWvhrKhuVjC99m4Q7BTmB3u60rhlE29rBEvwIIYS4bpIBqqiyUhwrLTccAC2H59+nKBkg28zBQbXVXCar3lGzHJ/apLZfsTSFFhyFzja3ULfn2HLiIuuOqJW0/9iTwOD6fWH3j+p+3zDOpFv43wkDA92gmW8qOp3Onh26t2tzanRvjBBCCFHSJANUUWUmOf5e81+1eGG+fa6RAbKY1bB1gAEfwG1T1N9/v+lY0LO688KnWrCaBNBS9zao1oY/9yTY75u99jhavV5o1kUUz+lDeeePA8SZ1SJ5vlnWfa2BWdO6tfH3NBaltkIIIUSxSABUUeUNbi4cgn2/5N/n8jUCoFObVPOXbeXxWyaoVYFtfMPzDZ+2dBjPiZAemPu/j8WisWyvIwCKPZXMyjgTu3Rqzaktl3z4X+xZzmihaoeM82p2attCqLaO0kIIIUQJkwCoojCbVFbG1t8nbwYIYPV/wWJx3pZ5jXmA9tkWzhzgWC+m23PQfbL6u0Gf/Es6hNQjtuZDEFCD2NPJxKdk4eNuYGgr1TfokW+2MS/7FgAuhkRjNOi4pXk98LDOr3PhcJ4AqJRnTBZCCFFpSABUUWz4FL7oCVvnqNu2AKhaW/Dwh8R9sHAkpJ1zPOZqGSCLxdH/p8kQ5/u6v8j5hzZi7vd+vmLEp2Sx8qyO+JQse/NXz8ZhPNa9HgC5Fo0l+p4cvncdDzz1Jgfe6M+nI6MhooU6wJltjiH5noHFfRWEEEKIIpEAqKJI3G/9vVf9tgVAwXXUIpF6IxxcCjM6QvwuFeDk7QR9ZQB0bo9asd3dl19SG/DfZQfJNasM0l/7z9H+s2M89N0ucnIdWaVdp5O587ON/HLSwMDp6/lpm1ruol/TcBqG+9GnSRh6Hbw/rBX1GzUDvcExkss2P41tTS1QTW9CCCHETSCjwCqKDOsCpOnn1W9bAOQdomb/DW8BPz+iAqSNM6Hf26DlaRK7sgnM2sn5YlALJiw6AECgt5EHO9fmP7/vR9NgtXUtrrfubM6vO8/w2pJ9XDaZMeo10rJUU5yHm57uDasA8MmI1lzKMBEeUMAq0RGt1O/jq9VvD3812kwIIYS4CeQKU1HYAh/bnD22/j3eIep3eDPo9iz89BBcPObc/AX2DNDBhDQem7eNt/QxdAQWnQuz7zI15hApl00cu5CBn6cbmTlmft5xhj/3JpCZo0aZda0XwoCgcyQFNmbGqmPc174mPh7qbebhZiA8oJC1smwZIFvgJh2ghRBC3EQSAFUUtgyQ7bc9AxTs2Me6VhcXj0GmtflLp1eZIGsGaP6mkxw7n0GA+y7Qw+acKFrXDESv07Ht5CU++fsIAM/0boCXu4EXFu0mM8dMRIAnozrVYnTHGsQs+5Nh3aJ4vGf9opc/pK5aN8xkXZNM+v8IIYS4iSQAqggsFsiwLi6anqhWYrdngPIEQEHWACgjUa3tBeAXCamn1Srt5lzWH03Cmywa6M8AcMqrEV+NbEPKZRMDP16L2aJRI9iLER1q4e6mJ8zfE7NF49YGVXAz6DGZTPan0105Quxq9AbVETpug7otI8CEEELcRNIJuiK4fBE060SHuVmQnercB8jGK9Bx2zaRYWAN+93nL13kcGI6zfXHMWDB5BPON08PISLAi0bh/jzdqz4GvY5Xb2+Ku5t663RvWJVejcNwK4kV2PMu1ClNYEIIIW4iyQBVBBnnnW+nny84AAI1KiwzCc5sV7d9w9QIMYuJ7YdPAdA74AxcBmONtlT1d3RYfqpXfR7rXhdjSQQ7BXEKgCQDJIQQ4uaRDFBFkJ54xe0ERyfnggIggPid1vuDwd0HgD3HVLNXZ09r81i16HxPddOCH5AASAghRKmRAKgiuDIDdOGwY4i7V7DzfbYAyJTpuN/DD4BDcfEAROUcVPdVa3MzSlu40IbgZs04SSdoIYQQN5EEQOVB6lnYNAuy0wq+/8oMkG1SRA9/xxIWNrYAyMY7GNx91dOkpVBFn4ZXhprAkMjWN1jwYjK4QVgzR7mEEEKIm0QCoPLgn7fhj+dh+7cF359xRQB03hoAFdSMdGUA5BUMHioA8uUyQ6pYFy8NbeCamZi7PQcNB0KDfqX/3EIIISoN6QRdHiSqmZi5cLDg+22TIBq9VdOWLQN0Zf8fKDADlGrxwB/wIYuuATmQgpo52hUa9lM/QgghxE0kGaDy4OIx9fvSiYLvt2WAqjax3rYGRAUFQF5BjpXXgZmbL7L+VDYAVTxyaB1o7RsUWPMGCy2EEEKUXRIAlXVZqZBpneSw0ADIGvCENXXefkUAdDb5MpMX7+a8e6R92w97M8hAdTye0DUC/xxrMOUfiRBCCFFRSQBU1l067vg7+RSYTfn3sTWB2ToQ21wRAL36616+33yKjcmODJDeO4TOjWsB4EO26nANEgAJIYSo0IocAP399980adKE1NTUfPelpKTQtGlT1qxZU6KFEziav0DN9pxy2vl+TXM0gYVfGQA5RlLtOp3Miv3n0OtAC1L9gCzo+P6pPkRUCVU75aRLACSEEKJSKHIANG3aNB5++GH8/f3z3RcQEMCjjz7K1KlTS7RwAucACPI3g2WlgDlH/Z2vCcwRAE2NOQTA0FbVGNzjFgD0XoFUDfCxjwLj8iXHavL+1Uqi9EIIIUSZVOQAKDY2ln79Ch+d06dPH7Zt21YihRJ5FBQAWSyw9Hn4+z+O/j8e/mrYet6h69YmsG0nL/HPwfMY9Dqe6lUfqjZW9wdUV7/d1USIJB0BNLU0hnfoTauSEEII4WpFHgZ/7tw5jEZj4Qdyc+P8+fOF3i+u00VrHyDvUNUZ+tJxSNgFm2ep7UGq/w4+1oDFp6rKCgF4h6BpGu/9qYbR39WmGrVDfYA2cOeXjkDIuhQGF1SWCP8I0Ev3MCGEEBVXka9y1apVY/fu3YXev2vXLiIiIkqkUCIPWwaobg/1+9IJOLnOcf+WL9Vvn6rqt2+Y4z7vEJbEnmXT8Yt4uOlV9semxd2OPkO2JjBb4CTNX0IIISq4IgdAAwYM4NVXXyUrKyvffZcvX+bf//43t99+e4kWrtLLyYQ0tT4XdXuq35dOwIk8AdDZHeq3bxXn30C6wZ///K4mRXyiRz2qB3kX/Dy2JjAb6QAthBCigityE9jLL7/Mzz//TIMGDXjiiSdo2LAhOp2O/fv38+mnn2I2m3nppZduZlkrH1uHZ89Ax7pcF09Aclz+fa0ZoCOXfahn3dRv1h4S03KpHeLNw93q5H+MjS0DZCMBkBBCiAquyBmgsLAw1q9fT7NmzZg8eTJ33HEHQ4cO5V//+hfNmjVj3bp1hIWFXftAV5gxYwZRUVF4enoSHR19zaH08+bNo2XLlnh7exMREcFDDz1EUlKS/f65c+ei0+ny/RSUuSrzbM1fwXUg0NrXJztFjdYyekONDo59fauSZTITc1IDIEXz5nRqLgCvDW6Kp9FQ+PPY+gDZSBOYEEKICq5Ya4HVqlWLpUuXcunSJY4cOYKmadSvX5+goAIW3SyChQsXMmHCBGbMmEGXLl2YNWsW/fv3Z9++fdSsmX8phrVr1/LAAw/w4YcfMmjQIM6cOcO4ceMYO3Ysixcvtu/n7+/PwYPO62Z5enpeVxldyh4ARYG7N/iGQ7p1sdIaHaDhADi1Sd32CWXOuuMcz/IBI3gHVuW5Vg0J9nGne8OqV38ed8kACSGEqFyKnAEym83s2rWLy5cvExQURLt27Wjfvj1BQUFkZmaya9cuLBZLsZ586tSpjBkzhrFjx9K4cWOmTZtGjRo1mDlzZoH7b9y4kdq1a/PUU08RFRXFLbfcwqOPPsrWrVud9tPpdISHhzv9lEt5M0AAQbUd99XqAo0H2W+mGYKYufIoxy2qrsaQKB7vUY/72hdhTS+PK/sASQZICCFExVbkDNC3337L9OnT2bRpU777PDw8+L//+z8mTJjA/fffX6Tj5eTksG3bNl588UWn7X369GH9+vUFPqZz58689NJLLF26lP79+5OYmMhPP/3EwIEDnfZLT0+nVq1amM1mWrVqxRtvvEHr1q0LLUt2djbZ2dn227bZrk0mEyZTAUtP3ADb8YpyXEPSUfRAbkAtNJMJQ2BN9Kc2ApBbvQOaVyiGhgPRHf2Llze7kZadS2Z4W0y3fQsRLaCoZdd7kHeCA5NX1aI/9grFqV95JXUs/yp6/UDqWBFU9PpBydexOMfRaZqmFWXHrl278vjjj3PvvfcWeP8PP/zA9OnTWb16dZGe+OzZs1SrVo1169bRuXNn+/a33nqLr7/+Ol8Tls1PP/3EQw89RFZWFrm5uQwePJiffvrJPkfRxo0bOXLkCM2bNyc1NZWPPvqIpUuXEhsbS/369Qs85muvvcaUKVPybZ8/fz7e3oWMnCoFvfdOwjvnAmvqv8RF34Y0jF9Mo4TFmHVGlrb4DIveSK7JxLeHzOxM9cVdr/F4EzO1/a59bCeaxqCdD6HHgoaO/7Wag6a7Sp8hIYQQogzKzMxkxIgRpKSkFLhyRV5FDoCqVq3K5s2bqV27doH3Hz9+nPbt2xd5MkRbALR+/Xo6depk3/6f//yHb7/9lgMHDuR7zL59+7jtttuYOHEiffv2JT4+nueee4527doxe/bsAp/HYrHQpk0bunXrxscff1zgPgVlgGrUqMGFCxeu+QIWl8lkIiYmht69e191Ykmy0zD+N0o9ZuIh8A5Gd+A33BaNxlKnB+b7fgRg4g+7+G13Aj7uBr4Y1YZ2ta+vP5bbB3XRZaWg+UWQ+1Th8z1dS5HrV45JHcu/il4/kDpWBBW9flDydUxNTSU0NLRIAVCRm8AyMjIKXAjVJi0tjczMzCIXMjQ0FIPBQEJCgtP2xMTEQkeTvf3223Tp0oXnnnsOgBYtWuDj40PXrl158803C5yIUa/X065dOw4fPlxoWTw8PPDw8Mi33Wg03rQ33TWPnXBU/fYNxxhgfT2aDgHLLPS1uqA3GknNMrFsn1q7a/bodnSsE1LIwYrA3Q+yUtD5VyuROt/M166skDqWfxW9fiB1rAgqev2g5OpYnGMUuRN0/fr1C+2bA2qEVmFNTAVxd3cnOjqamJgYp+0xMTFOTWJ5ZWZmor9iiQaDQTXVFJbI0jSNnTt3lr9ZqhP3qd9hTRzb9HpoeS8E1gBg9aHzmMwadar43FjwA465gGQEmBBCiEqgyAHQiBEjePnll9m1a1e++2JjY3n11VcZMWJEsZ580qRJfPnll8yZM4f9+/czceJE4uLiGDduHACTJ0/mgQcesO8/aNAgfv75Z2bOnMmxY8dYt24dTz31FO3btycyUl24p0yZwrJlyzh27Bg7d+5kzJgx7Ny5037McsMWAFVtUuguf+1PBOC2xsWffykf21xAMgJMCCFEJVDkJrCJEyfyxx9/EB0dzW233UajRo3sM0GvWLGCzp07M3HixGI9+fDhw0lKSuL1118nPj6eZs2asXTpUmrVUpP+xcfHExfnmPV49OjRpKWlMX36dJ555hkCAwPp2bMn7777rn2f5ORkHnnkERISEggICKB169asXr2a9u3bF6tsLldIAHQhPZtgb3csmsbKgyoA6tXoGvP8FIW7ZICEEEJUHkUOgIxGI8uXL+fDDz9k/vz5rF69Gk3TaNCgAf/5z3+YOHEie/fupVWrVsUqwPjx4xk/fnyB982dOzfftieffJInn3yy0ON9+OGHfPjhh8UqQ5mUqNbwsq/YDuyIu8QdM9bTrUEVxnWrQ3KmiQAvI9G1rq/js5OaHdUiq7UKbn4UQgghKpIiN4GBCoKef/55du7cSUZGBpmZmfzzzz/4+vrSsWNHoqOjb1Y5K5f085BxHtBBlUb2zZuOXwRU35/H528HoEfDKrgZinUaC9bjX/BiHFRve+PHEkIIIcq4675y/v3339x///1ERkbyySef0L9//3wzMovrZGv+si2BYXUyKcP+96VMNdlTr5Lo/2Nz5ZpgQgghRAVVrLXATp8+zdy5c5kzZw4ZGRncc889mEwmFi1aRJMmhXfWFcVUSP+fk0lqmoEOUcFsOn4Rd4Oebg2qlHbphBBCiHKvyAHQgAEDWLt2LbfffjuffPIJ/fr1w2Aw8Nlnn93M8lVO9gCosdNmWwD0fL9GnL6USaC3OwFeFXtuCCGEEOJmKHIAtHz5cp566ikee+yxYs33I66DvQO0IwOUnWvmbMplAGqFeJdMx2chhBCikipyH6A1a9aQlpZG27Zt6dChA9OnTy/ysheiGCyWAgOgUxcvo2ng6+FGiI+7iwonhBBCVAxFDoA6derEF198QXx8PI8++igLFiygWrVqWCwWYmJiSEtLu5nlrDxSz0BOOuiNEFLXvtnWAbpWiDc6nc5VpRNCCCEqhGKPAvP29ub//u//WLt2Lbt37+aZZ57hnXfeoWrVqgwePPhmlLFyybygfvtWBYOjf88Ja/+fWiGuW51eCCGEqChuaAKZhg0b8t5773H69Gm+//77kipT5ZZlXXDWw89pc5w9AyRD1YUQQogbVQIz6KkFSYcOHcqSJUtK4nCVW7a1KdHD32mzLQNUWzJAQgghxA0rkQBIlKDsgjNAtj5ANYMlAySEEELcKAmAyhpbBsjTkQHKNVs4fUkNga8dKhkgIYQQ4kZJAFTWFNAH6GxyFrkWDQ83PWF+ni4qmBBCCFFxSABU1tibwBwZoBP25i9v9HoZAi+EEELcKAmAypoCAqCTF21D4KX/jxBCCFESirUYqigFefoAfbryCAu3nOJiRg4gI8CEEEKIkiIBUFlj7QOU6+bLx38dJjvXYr+rY50QV5VKCCGEqFAkACprrBmg05fdyM61EOhtZP7YjoT4uhPmLx2ghRBCiJIgAVBZY+0DdOCSutm6RiBNIv2v8gAhhBBCFJd0gi5rrBmg3dYlwdrUDHJhYYQQQoiKSQKgssbaB2h7Qi4AbWpJACSEEEKUNAmAyhJNszeBHUnVo9dByxqBri2TEEIIUQFJAFSW5KQDGgBpeNEgzA9fD+mmJYQQQpQ0CYDKEmv/H7POQBbu0vwlhBBC3CQSAJUl1v4/mXgDOukALYQQQtwkEgCVJdYMULLFC4A2NQNdWBghhBCi4pIAqCzJTgEgTfMiwMtIVKis/SWEEELcDBIAlSXWDFAaXjQM80Onk5XfhRBCiJtBAqCyxNoHKE3zom5VXxcXRgghhKi4JAAqS+wZIG/qSQAkhBBC3DQSAJUl1kkQ0zUv6ksAJIQQQtw0EgCVIWZrE1g6XpIBEkIIIW4iCYBczXQZTm8DTSMj5SIAWXofIgI8XVwwIYQQouKSAMjVlr0EX/aEg0vJTLsEgLdfkIwAE0IIIW4iCYBcLemI+h23gZyMZAB8A4JdVx4hhBCiEpAAyNWy1OSHJO7HkqVGgQUHh7qwQEIIIUTFJ0uNu5p15Bfn9mHIUfFoldAqLiyQEEIIUfFJAORq1pFfpJ0lWPMAHUSESQAkhBBC3EzSBOZqtgwQ4KPLBiCsSlVXlUYIIYSoFCQAciVTFphz8m128wpwQWGEEEKIykMCIFfKk/1x4uFXuuUQQgghKhkJgFwpK38AlKv3ADd3FxRGCCGEqDwkAHKl7JR8m3KNsgSGEEIIcbNJAORKtgxQcF1yradC5+HvwgIJIYQQlYMEQK5k7QOU6xXKCUs4AG7e0gFaCCGEuNkkAHIlawYoQ+fNQa06AAYvyQAJIYQQN5sEQK5kzQClaF4cstRQ26QJTAghhLjpJAByJWsG6GKuJ79YunDSpzm0vt/FhRJCCCEqPgmAXMm6EGpCtjsntXD+6vQtNOzv4kIJIYQQFZ8EQK5kbQI7e9kIQJ0qPq4sjRBCCFFpuDwAmjFjBlFRUXh6ehIdHc2aNWuuuv+8efNo2bIl3t7eRERE8NBDD5GUlOS0z6JFi2jSpAkeHh40adKExYsX38wqXD9rBiguUwVAdavIHEBCCCFEaXBpALRw4UImTJjASy+9xI4dO+jatSv9+/cnLi6uwP3Xrl3LAw88wJgxY9i7dy8//vgjW7ZsYezYsfZ9NmzYwPDhwxk1ahSxsbGMGjWKe+65h02bNpVWtYrOmgG6ZPbE3U1PZKCXiwskhBBCVA4uDYCmTp3KmDFjGDt2LI0bN2batGnUqFGDmTNnFrj/xo0bqV27Nk899RRRUVHccsstPProo2zdutW+z7Rp0+jduzeTJ0+mUaNGTJ48mV69ejFt2rRSqlUxWDtBp+FNVIgPBr3OxQUSQgghKgeXBUA5OTls27aNPn36OG3v06cP69evL/AxnTt35vTp0yxduhRN0zh37hw//fQTAwcOtO+zYcOGfMfs27dvocd0KWsGKE3zlv4/QgghRClyc9UTX7hwAbPZTFhYmNP2sLAwEhISCnxM586dmTdvHsOHDycrK4vc3FwGDx7MJ598Yt8nISGhWMcEyM7OJjs72347NVUFJiaTCZPJVOy6XY3teCaTCbesVHRAKt60DfEq8edyhbz1q6ikjuVfRa8fSB0rgopePyj5OhbnOC4LgGx0OudmH03T8m2z2bdvH0899RSvvvoqffv2JT4+nueee45x48Yxe/bs6zomwNtvv82UKVPybV++fDne3t7FqU6RxcTEcPvlZAyoDFDy6SMsXXr4pjyXK8TExLi6CDed1LH8q+j1A6ljRVDR6wclV8fMzMwi7+uyACg0NBSDwZAvM5OYmJgvg2Pz9ttv06VLF5577jkAWrRogY+PD127duXNN98kIiKC8PDwYh0TYPLkyUyaNMl+OzU1lRo1atCnTx/8/Ut2ZmaTyURMTAy9e3TFsCMXUH2AundqS8+GVUr0uVzBXr/evTEaja4uzk0hdSz/Knr9QOpYEVT0+kHJ19HWglMULguA3N3diY6OJiYmhjvuuMO+PSYmhiFDhhT4mMzMTNzcnItsMBgAleUB6NSpEzExMUycONG+z/Lly+ncuXOhZfHw8MDDwyPfdqPReNPedEbzZQAs6EjHk6r+XhXqDX4zX7uyQupY/lX0+oHUsSKo6PWDkqtjcY7h0iawSZMmMWrUKNq2bUunTp34/PPPiYuLY9y4cYDKzJw5c4ZvvvkGgEGDBvHwww8zc+ZMexPYhAkTaN++PZGRkQA8/fTTdOvWjXfffZchQ4bw66+/smLFCtauXeuyehbI2gE6Q/NEQ0+wj7uLCySEEEJUHi4NgIYPH05SUhKvv/468fHxNGvWjKVLl1KrVi0A4uPjneYEGj16NGlpaUyfPp1nnnmGwMBAevbsybvvvmvfp3PnzixYsICXX36ZV155hbp167Jw4UI6dOhQ6vW7Gp01AEpF9TGSAEgIIYQoPS7vBD1+/HjGjx9f4H1z587Nt+3JJ5/kySefvOoxhw0bxrBhw0qieDdPdhqgOkAbDTp8PVx+KoQQQohKw+VLYVRatjmA8CLI2/2qo9SEEEIIUbIkAHIV6zpgaZq3NH8JIYQQpUwCIBfRZTuWwZAASAghhChdEgC5im0dMM1LAiAhhBCilEkA5Cq2TtCSARJCCCFKnQRALqLLsxCqBEBCCCFE6ZIAyFXyzAMkAZAQQghRuiQAcpVsRx+gIG8JgIQQQojSJAGQq2TZMkA+hEgGSAghhChVEgC5iC5vBkgCICGEEKJUSQDkKnlGgUkGSAghhChdEgC5gmaBrGQAUjQfAqUPkBBCCFGqJAByAY/cVHSWXMyajizPUNzd5DQIIYQQpUmuvC7glXMRgESCCPDxcnFphBBCiMpHAiAX8DKpAChBC5Yh8EIIIYQLSADkAp7WACheC5YO0EIIIYQLSADkAl45lwBrBkgCICGEEKLUSQDkApIBEkIIIVxLAiAXcOoDJAGQEEIIUeokAHIBWxNYvBYsC6EKIYQQLiABUGnTNDxN1j5AhBAso8CEEEKIUicBUGm7fBGDZgLgnBYkTWBCCCGEC0gAVNpSzwJwQQvAhJs0gQkhhBAuIAFQKdOlqQAoXgsCwNvd4MriCCGEEJWSBEClTGfNACVoIQB4ukkAJIQQQpQ2CYBKW1o8oEaAAXgY5RQIIYQQpU2uvqXM1gSWYAuAZCV4IYQQotTJ1be0pdr6AAXj7qZHp9O5uEBCCCFE5SMBUCmzZ4AIxlOyP0IIIYRLyBW4NGkapDr6AHkYpQO0EEII4QoSAJWm7FR0pgxA9QHylA7QQgghhEvIFbg0Wfv/XNb7koUHHjIEXgghhHAJCYBKU1oCAKkGNQmijAATQgghXEOuwKWpbg9Mz8cxr8pzAHhKHyAhhBDCJSQAKm1Gby7pJQMkhBBCuJJcgV0gV1O/JQMkhBBCuIYEQC5gsqjfkgESQgghXEOuwC5gC4AkAySEEEK4hgRALiAZICGEEMK15ArsArkWtf6XZICEEEII15AAyAUkAySEEEK4llyBXcAeAEkGSAghhHAJCYBcQDJAQgghhGvJFdgFJAASQgghXEuuwC4gEyEKIYQQriUBkAtIBkgIIYRwLbkCu4BMhCiEEEK4lgRALmCyzgMkGSAhhBDCNeQK7AK5kgESQgghXEoCIBeQPkBCCCGEa8kV2AWkD5AQQgjhWi4PgGbMmEFUVBSenp5ER0ezZs2aQvcdPXo0Op0u30/Tpk3t+8ydO7fAfbKyskqjOkVisg6D9zC6/OUXQgghKiWXXoEXLlzIhAkTeOmll9ixYwddu3alf//+xMXFFbj/Rx99RHx8vP3n1KlTBAcHc/fddzvt5+/v77RffHw8np6epVGlIrFngNwkAySEEEK4gksDoKlTpzJmzBjGjh1L48aNmTZtGjVq1GDmzJkF7h8QEEB4eLj9Z+vWrVy6dImHHnrIaT+dTue0X3h4eGlUp8hy7WuBSQZICCGEcAU3Vz1xTk4O27Zt48UXX3Ta3qdPH9avX1+kY8yePZvbbruNWrVqOW1PT0+nVq1amM1mWrVqxRtvvEHr1q0LPU52djbZ2dn226mpqQCYTCZMJlNRq1QkWdk5mDU1DN6ApcSP72q2+lS0euUldSz/Knr9QOpYEVT0+kHJ17E4x9FpmqaVyLMW09mzZ6lWrRrr1q2jc+fO9u1vvfUWX3/9NQcPHrzq4+Pj46lRowbz58/nnnvusW/fuHEjR44coXnz5qSmpvLRRx+xdOlSYmNjqV+/foHHeu2115gyZUq+7fPnz8fb2/s6a1iwbDM8v1nFne+1z8VDWsGEEEKIEpGZmcmIESNISUnB39//qvu6LANko9PpnG5rmpZvW0Hmzp1LYGAgQ4cOddresWNHOnbsaL/dpUsX2rRpwyeffMLHH39c4LEmT57MpEmT7LdTU1OpUaMGffr0ueYLWFyJKRmweR0Agwf2x6C/dl3LE5PJRExMDL1798ZoNLq6ODeF1LH8q+j1A6ljRVDR6wclX0dbC05RuCwACg0NxWAwkJCQ4LQ9MTGRsLCwqz5W0zTmzJnDqFGjcHd3v+q+er2edu3acfjw4UL38fDwwMPDI992o9FY4m86MyrlYzTo8PS4etnLs5vx2pU1Usfyr6LXD6SOFUFFrx+UXB2LcwyX9cJ1d3cnOjqamJgYp+0xMTFOTWIFWbVqFUeOHGHMmDHXfB5N09i5cycRERE3VN6Skp1rBsBdJkEUQgghXMalTWCTJk1i1KhRtG3blk6dOvH5558TFxfHuHHjANU0debMGb755hunx82ePZsOHTrQrFmzfMecMmUKHTt2pH79+qSmpvLxxx+zc+dOPv3001Kp07VkW8fAyxB4IYQQwnVcGgANHz6cpKQkXn/9deLj42nWrBlLly61j+qKj4/PNydQSkoKixYt4qOPPirwmMnJyTzyyCMkJCQQEBBA69atWb16Ne3bt7/p9SmKbOsYeFkGQwghhHAdl3eCHj9+POPHjy/wvrlz5+bbFhAQQGZmZqHH+/DDD/nwww9LqnglLsvaBOYpcwAJIYQQLiNX4VJmywC5SxOYEEII4TISAJUyex8gyQAJIYQQLiNX4VImfYCEEEII15OrcCnLMln7AEkTmBBCCOEyEgCVMkcfIHnphRBCCFeRq3ApkyYwIYQQwvXkKlzKsm1NYEZpAhNCCCFcRQKgUpYlGSAhhBDC5eQqXMpsTWAyDF4IIYRwHbkKlzLpBC2EEEK4nlyFS1m2DIMXQgghXE4CoFJmHwUmTWBCCCGEy8hVuJQ5JkKUl14IIYRwFbkKlzJZDFUIIYRwPQmASpmMAhNCCCFcT67CpUxmghZCCCFcT67CpSxLZoIWQgghXE4CoFImGSAhhBDC9eQqXMps8wDJRIhCCCGE68hVuJTZO0HLKDAhhBDCZSQAKmXSBCaEEEK4nlyFS1mWDIMXQgghXE6uwqVI0zRyJAMkhBBCuJxchUuRrfkLwEOGwQshhBAuIwFQKco25QmAJAMkhBBCuIxchUtRVq4aAq9Hw2iQl14IIYRwFbkKlyJbBkiSP0IIIYRryaW4FNkyQDIATAghhHAtuRSXIlsGSAIgIYQQwrXkUlyKbBkgaQITQgghXEsuxaWoQZgf3zwUzX11za4uihBCCFGpSQBUigK8jHSqE0I9f1eXRAghhKjcJAASQgghRKUjAZAQQgghKh0JgIQQQghR6UgAJIQQQohKRwIgIYQQQlQ6EgAJIYQQotKRAEgIIYQQlY4EQEIIIYSodCQAEkIIIUSlIwGQEEIIISodCYCEEEIIUelIACSEEEKISkcCICGEEEJUOhIACSGEEKLSkQBICCGEEJWOBEBCCCGEqHQkABJCCCFEpSMBkBBCCCEqHQmAhBBCCFHpuDwAmjFjBlFRUXh6ehIdHc2aNWsK3Xf06NHodLp8P02bNnXab9GiRTRp0gQPDw+aNGnC4sWLb3Y1hBBCCFGOuDQAWrhwIRMmTOCll15ix44ddO3alf79+xMXF1fg/h999BHx8fH2n1OnThEcHMzdd99t32fDhg0MHz6cUaNGERsby6hRo7jnnnvYtGlTaVVLCCGEEGWcSwOgqVOnMmbMGMaOHUvjxo2ZNm0aNWrUYObMmQXuHxAQQHh4uP1n69atXLp0iYceesi+z7Rp0+jduzeTJ0+mUaNGTJ48mV69ejFt2rRSqpUQQgghyjo3Vz1xTk4O27Zt48UXX3Ta3qdPH9avX1+kY8yePZvbbruNWrVq2bdt2LCBiRMnOu3Xt2/fqwZA2dnZZGdn22+npKQAcPHiRUwmU5HKUlQmk4nMzEySkpIwGo0leuyyoKLXD6SOFUFFrx9IHSuCil4/KPk6pqWlAaBp2jX3dVkAdOHCBcxmM2FhYU7bw8LCSEhIuObj4+Pj+eOPP5g/f77T9oSEhGIf8+2332bKlCn5tkdFRV2zHEIIIYQoW9LS0ggICLjqPi4LgGx0Op3TbU3T8m0ryNy5cwkMDGTo0KE3fMzJkyczadIk+22LxcLFixcJCQkpUlmKIzU1lRo1anDq1Cn8/f1L9NhlQUWvH0gdK4KKXj+QOlYEFb1+UPJ11DSNtLQ0IiMjr7mvywKg0NBQDAZDvsxMYmJivgzOlTRNY86cOYwaNQp3d3en+8LDw4t9TA8PDzw8PJy2BQYGFqEW18/f37/CvqGh4tcPpI4VQUWvH0gdK4KKXj8o2TpeK/Nj47JO0O7u7kRHRxMTE+O0PSYmhs6dO1/1satWreLIkSOMGTMm332dOnXKd8zly5df85hCCCGEqDxc2gQ2adIkRo0aRdu2benUqROff/45cXFxjBs3DlBNU2fOnOGbb75xetzs2bPp0KEDzZo1y3fMp59+mm7duvHuu+8yZMgQfv31V1asWMHatWtLpU5CCCGEKPtcGgANHz6cpKQkXn/9deLj42nWrBlLly61j+qKj4/PNydQSkoKixYt4qOPPirwmJ07d2bBggW8/PLLvPLKK9StW5eFCxfSoUOHm16fovDw8ODf//53via3iqKi1w+kjhVBRa8fSB0rgopeP3BtHXVaUcaKCSGEEEJUIC5fCkMIIYQQorRJACSEEEKISkcCICGEEEJUOhIACSGEEKLSkQCoFM2YMYOoqCg8PT2Jjo5mzZo1ri7SdXv77bdp164dfn5+VK1alaFDh3Lw4EGnfUaPHo1Op3P66dixo4tKXDyvvfZavrKHh4fb79c0jddee43IyEi8vLzo3r07e/fudWGJi6927dr56qjT6Xj88ceB8nn+Vq9ezaBBg4iMjESn0/HLL7843V+U85adnc2TTz5JaGgoPj4+DB48mNOnT5diLQp3tfqZTCZeeOEFmjdvjo+PD5GRkTzwwAOcPXvW6Rjdu3fPd17vvffeUq5J4a51DovyvizL5xCuXceCPpc6nY7333/fvk9ZPo9FuT6Uhc+iBEClZOHChUyYMIGXXnqJHTt20LVrV/r3759vmH95sWrVKh5//HE2btxITEwMubm59OnTh4yMDKf9+vXrR3x8vP1n6dKlLipx8TVt2tSp7Lt377bf99577zF16lSmT5/Oli1bCA8Pp3fv3vaF+MqDLVu2ONXPNoHo3Xffbd+nvJ2/jIwMWrZsyfTp0wu8vyjnbcKECSxevJgFCxawdu1a0tPTuf322zGbzaVVjUJdrX6ZmZls376dV155he3bt/Pzzz9z6NAhBg8enG/fhx9+2Om8zpo1qzSKXyTXOodw7fdlWT6HcO065q1bfHw8c+bMQafTcddddzntV1bPY1GuD2Xis6iJUtG+fXtt3LhxTtsaNWqkvfjiiy4qUclKTEzUAG3VqlX2bQ8++KA2ZMgQ1xXqBvz73//WWrZsWeB9FotFCw8P19555x37tqysLC0gIED77LPPSqmEJe/pp5/W6tatq1ksFk3Tyvf50zRNA7TFixfbbxflvCUnJ2tGo1FbsGCBfZ8zZ85oer1e+/PPP0ut7EVxZf0KsnnzZg3QTp48ad926623ak8//fTNLVwJKaiO13pflqdzqGlFO49DhgzRevbs6bStPJ3HK68PZeWzKBmgUpCTk8O2bdvo06eP0/Y+ffqwfv16F5WqZKWkpAAQHBzstP2ff/6hatWqNGjQgIcffpjExERXFO+6HD58mMjISKKiorj33ns5duwYAMePHychIcHpfHp4eHDrrbeW2/OZk5PDd999x//93/85LQBcns/flYpy3rZt24bJZHLaJzIykmbNmpXLc5uSkoJOp8u3tuG8efMIDQ2ladOmPPvss+UqcwlXf19WtHN47tw5fv/99wKXfiov5/HK60NZ+Sy6fDX4yuDChQuYzeZ8C7KGhYXlW7i1PNI0jUmTJnHLLbc4LU/Sv39/7r77bmrVqsXx48d55ZVX6NmzJ9u2bSvzM5t26NCBb775hgYNGnDu3DnefPNNOnfuzN69e+3nrKDzefLkSVcU94b98ssvJCcnM3r0aPu28nz+ClKU85aQkIC7uztBQUH59ilvn9WsrCxefPFFRowY4bTI5MiRI4mKiiI8PJw9e/YwefJkYmNj862hWFZd631Zkc4hwNdff42fnx933nmn0/bych4Luj6Ulc+iBEClKO83a1BvjCu3lUdPPPEEu3btyrfe2vDhw+1/N2vWjLZt21KrVi1+//33fB/msqZ///72v5s3b06nTp2oW7cuX3/9tb3DZUU6n7Nnz6Z///5ERkbat5Xn83c113Peytu5NZlM3HvvvVgsFmbMmOF038MPP2z/u1mzZtSvX5+2bduyfft22rRpU9pFLbbrfV+Wt3NoM2fOHEaOHImnp6fT9vJyHgu7PoDrP4vSBFYKQkNDMRgM+aLWxMTEfBFwefPkk0+yZMkSVq5cSfXq1a+6b0REBLVq1eLw4cOlVLqS4+PjQ/PmzTl8+LB9NFhFOZ8nT55kxYoVjB079qr7lefzBxTpvIWHh5OTk8OlS5cK3aesM5lM3HPPPRw/fpyYmBin7E9B2rRpg9FoLLfn9cr3ZUU4hzZr1qzh4MGD1/xsQtk8j4VdH8rKZ1ECoFLg7u5OdHR0vtRkTEwMnTt3dlGpboymaTzxxBP8/PPP/P3330RFRV3zMUlJSZw6dYqIiIhSKGHJys7OZv/+/URERNjTznnPZ05ODqtWrSqX5/Orr76iatWqDBw48Kr7lefzBxTpvEVHR2M0Gp32iY+PZ8+ePeXi3NqCn8OHD7NixQpCQkKu+Zi9e/diMpnK7Xm98n1Z3s9hXrNnzyY6OpqWLVtec9+ydB6vdX0oM5/FEulKLa5pwYIFmtFo1GbPnq3t27dPmzBhgubj46OdOHHC1UW7Lo899pgWEBCg/fPPP1p8fLz9JzMzU9M0TUtLS9OeeeYZbf369drx48e1lStXap06ddKqVaumpaamurj01/bMM89o//zzj3bs2DFt48aN2u233675+fnZz9c777yjBQQEaD///LO2e/du7b777tMiIiLKRd3yMpvNWs2aNbUXXnjBaXt5PX9paWnajh07tB07dmiANnXqVG3Hjh32UVBFOW/jxo3Tqlevrq1YsULbvn271rNnT61ly5Zabm6uq6pld7X6mUwmbfDgwVr16tW1nTt3On0us7OzNU3TtCNHjmhTpkzRtmzZoh0/flz7/ffftUaNGmmtW7cuE/XTtKvXsajvy7J8DjXt2u9TTdO0lJQUzdvbW5s5c2a+x5f183it64OmlY3PogRApejTTz/VatWqpbm7u2tt2rRxGjJe3gAF/nz11VeapmlaZmam1qdPH61KlSqa0WjUatasqT344INaXFycawteRMOHD9ciIiI0o9GoRUZGanfeeae2d+9e+/0Wi0X797//rYWHh2seHh5at27dtN27d7uwxNdn2bJlGqAdPHjQaXt5PX8rV64s8H354IMPappWtPN2+fJl7YknntCCg4M1Ly8v7fbbby8z9b5a/Y4fP17o53LlypWapmlaXFyc1q1bNy04OFhzd3fX6tatqz311FNaUlKSayuWx9XqWNT3ZVk+h5p27feppmnarFmzNC8vLy05OTnf48v6ebzW9UHTysZnUWctrBBCCCFEpSF9gIQQQghR6UgAJIQQQohKRwIgIYQQQlQ6EgAJIYQQotKRAEgIIYQQlY4EQEIIIYSodCQAEkIIIUSlIwGQEEIUgU6n45dffnF1MYQQJUQCICFEmTd69Gh0Ol2+n379+rm6aEKIcsrN1QUQQoii6NevH1999ZXTNg8PDxeVRghR3kkGSAhRLnh4eBAeHu70ExQUBKjmqZkzZ9K/f3+8vLyIiorixx9/dHr87t276dmzJ15eXoSEhPDII4+Qnp7utM+cOXNo2rQpHh4eRERE8MQTTzjdf+HCBe644w68vb2pX78+S5YsubmVFkLcNBIACSEqhFdeeYW77rqL2NhY7r//fu677z72798PQGZmJv369SMoKIgtW7bw448/smLFCqcAZ+bMmTz++OM88sgj7N69myVLllCvXj2n55gyZQr33HMPu3btYsCAAYwcOZKLFy+Waj2FECWkxJZVFUKIm+TBBx/UDAaD5uPj4/Tz+uuva5qmVp8eN26c02M6dOigPfbYY5qmadrnn3+uBQUFaenp6fb7f//9d02v12sJCQmapmlaZGSk9tJLLxVaBkB7+eWX7bfT09M1nU6n/fHHHyVWTyFE6ZE+QEKIcqFHjx7MnDnTaVtwcLD9706dOjnd16lTJ3bu3AnA/v37admyJT4+Pvb7u3TpgsVi4eDBg+h0Os6ePUuvXr2uWoYWLVrY//bx8cHPz4/ExMTrrZIQwoUkABJClAs+Pj75mqSuRafTAaBpmv3vgvbx8vIq0vGMRmO+x1oslmKVSQhRNkgfICFEhbBx48Z8txs1agRAkyZN2LlzJxkZGfb7161bh16vp0GDBvj5+VG7dm3++uuvUi2zEMJ1JAMkhCgXsrOzSUhIcNrm5uZGaGgoAD/++CNt27bllltuYd68eWzevJnZs2cDMHLkSP7973/z4IMP8tprr3H+/HmefPJJRo0aRVhYGACvvfYa48aNo2rVqvTv35+0tDTWrVvHk08+WboVFUKUCgmAhBDlwp9//klERITTtoYNG3LgwAFAjdBasGAB48ePJzw8nHnz5tGkSRMAvL29WbZsGU8//TTt2rXD29ubu+66i6lTp9qP9eCDD5KVlcWHH37Is88+S2hoKMOGDSu9CgohSpVO0zTN1YUQQogbodPpWLx4MUOHDnV1UYQQ5YT0ARJCCCFEpSMBkBBCCCEqHekDJIQo96QlXwhRXJIBEkIIIUSlIwGQEEIIISodCYCEEEIIUelIACSEEEKISkcCICGEEEJUOhIACSGEEKLSkQBICCGEEJWOBEBCCCGEqHQkABJCCCFEpfP/0667Tn9e5G0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Plot\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "metrics = pd.read_csv(f\"{trainer.logger.log_dir}/metrics.csv\")\n",
    "\n",
    "aggreg_metrics = []\n",
    "agg_col = \"epoch\"\n",
    "for i, dfg in metrics.groupby(agg_col):\n",
    "    agg = dict(dfg.mean())\n",
    "    agg[agg_col] = i\n",
    "    aggreg_metrics.append(agg)\n",
    "\n",
    "df_metrics = pd.DataFrame(aggreg_metrics)\n",
    "df_metrics[[\"train_loss\", \"val_loss\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"Loss\"\n",
    ")\n",
    "\n",
    "\n",
    "df_metrics[[\"train_acc\", \"val_acc\"]].plot(\n",
    "    grid=True, legend=True, xlabel=\"Epoch\", ylabel=\"ACC\"\n",
    ")\n",
    "\n",
    "plt.ylim([0.7, 1.0])\n",
    "\n",
    "plt.savefig('4-cosine-epoch-decay_acc.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0df61ef8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at logs/my-model/version_13/checkpoints/epoch=110-step=49950.ckpt\n",
      "Loaded model weights from checkpoint at logs/my-model/version_13/checkpoints/epoch=110-step=49950.ckpt\n",
      "/Users/sebastianraschka/miniforge3/envs/dl-fundamentals/lib/python3.9/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:231: PossibleUserWarning: The dataloader, test_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 10 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.\n",
      "  rank_zero_warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e0c4507630c34b82bcb539ec7a6ad390",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">         test_acc          </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8897500038146973     </span>│\n",
       "└───────────────────────────┴───────────────────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36m        test_acc         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8897500038146973    \u001b[0m\u001b[35m \u001b[0m│\n",
       "└───────────────────────────┴───────────────────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[{'test_acc': 0.8897500038146973}]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=lightning_model, datamodule=dm, ckpt_path=\"best\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1c17a3c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Restoring states from the checkpoint path at logs/my-model/version_13/checkpoints/last.ckpt\n",
      "Loaded model weights from checkpoint at logs/my-model/version_13/checkpoints/last.ckpt\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "651b7cce6a7c4df7a3aaf5a104ebdf6a",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Testing: 0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\">        Test metric        </span>┃<span style=\"font-weight: bold\">       DataLoader 0        </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│<span style=\"color: #008080; text-decoration-color: #008080\">         test_acc          </span>│<span style=\"color: #800080; text-decoration-color: #800080\">    0.8922500014305115     </span>│\n",
       "└───────────────────────────┴───────────────────────────┘\n",
       "</pre>\n"
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       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1m       Test metric       \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      DataLoader 0       \u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
       "│\u001b[36m \u001b[0m\u001b[36m        test_acc         \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m   0.8922500014305115    \u001b[0m\u001b[35m \u001b[0m│\n",
       "└───────────────────────────┴───────────────────────────┘\n"
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       "[{'test_acc': 0.8922500014305115}]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainer.test(model=lightning_model, datamodule=dm, ckpt_path=\"last\")"
   ]
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   "execution_count": null,
   "id": "3980ed55-59c7-460d-a8ee-7e7ffd5b2ffe",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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